ABSTRACT
When fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools and processing pipelines. We provide a critical evaluation of the impact of differences across five independently developed minimal preprocessing pipelines for functional magnetic resonance imaging. We show that, even when handling identical data, interpipeline agreement was only moderate, critically shedding light on a factor that limits cross-study reproducibility. We show that low interpipeline agreement can go unrecognized until the reliability of the underlying data is high, which is increasingly the case as the field progresses. Crucially we show that, when interpipeline agreement is compromised, so too is the consistency of insights from brain-wide association studies. We highlight the importance of comparing analytic configurations, because both widely discussed and commonly overlooked decisions can lead to marked variation.
ABSTRACT
Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence1-6. The brain's capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity7-12, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortex's sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.
ABSTRACT
Brain connectome analysis suffers from the high dimensionality of connectivity data, often forcing a reduced representation of the brain at a lower spatial resolution or parcellation. This is particularly true for graph-based representations, which are increasingly used to characterize connectivity gradients, capturing patterns of systematic spatial variation in the functional connectivity structure. However, maintaining a high spatial resolution is crucial for enabling fine-grained topographical analysis and preserving subtle individual differences that might otherwise be lost. Here we introduce a computationally efficient approach to establish spatially fine-grained connectivity gradients. At its core, it leverages a set of landmarks to approximate the underlying connectivity structure at the full spatial resolution without requiring a full-scale vertex-by-vertex connectivity matrix. We show that this approach reduces computational time and memory usage while preserving informative individual features and demonstrate its application in improving brain-behavior predictions. Overall, its efficiency can remove computational barriers and enable the widespread application of connectivity gradients to capture spatial signatures of the connectome. Importantly, maintaining a spatially fine-grained resolution facilitates to characterize the spatial transitions inherent in the core concept of gradients of brain organization.
Subject(s)
Brain , Connectome , Brain/physiology , Brain/diagnostic imaging , Humans , Male , Female , Nerve Net/physiology , Magnetic Resonance Imaging/methods , AdultABSTRACT
The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.
Subject(s)
Cerebral Cortex , Neural Pathways , Thalamus , Humans , Thalamus/physiology , Male , Child , Female , Adolescent , Cerebral Cortex/physiology , Neural Pathways/physiology , Magnetic Resonance Imaging , Infant , Child, Preschool , Nerve Net/physiology , Cross-Sectional Studies , Longitudinal StudiesABSTRACT
Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.
Subject(s)
Connectome , Magnetic Resonance Imaging , Sensorimotor Cortex , Humans , Adolescent , Female , Male , Young Adult , Child , Sensorimotor Cortex/physiology , Sensorimotor Cortex/diagnostic imaging , Child, Preschool , Nerve Net/physiology , Nerve Net/diagnostic imaging , Neural Pathways/physiology , Adult , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/physiology , Cerebral Cortex/growth & developmentABSTRACT
The Child and Adolescent Mental Health Initiative (CAMHI) aims to enhance mental health care capacity for children and adolescents across Greece. Considering the need for evidence-based policy, the program developed an open-resource dataset for researching the field within the country. A comprehensive, mixed-method, community-based research was conducted in 2022/2023 assessing the current state, needs, barriers, and opportunities according to multiple viewpoints. We surveyed geographically distributed samples of 1,756 caregivers, 1,201 children/adolescents, 404 schoolteachers, and 475 health professionals using validated instruments to assess mental health symptoms, mental health needs, literacy and stigma, service use and access, professional practices, training background, and training needs and preferences. Fourteen focus groups were conducted with informants from diverse populations (including underrepresented minorities) to reach an in-depth understanding of those topics. A dataset with quantitative and qualitative findings is now available for researchers, policymakers, and society [ https://osf.io/crz6h/ and https://rpubs.com/camhi/sdashboard ]. This resource offers valuable data for assessing the needs and priorities for child and adolescent mental health care in Greece. It is now freely available to consult, and is expected to inform upcoming research and evidence-based professional training. This initiative may inspire similar ones in other countries, informing methodological strategies for researching mental health needs.
ABSTRACT
Cognitive science has demonstrated that we construct knowledge about the world by abstracting patterns from routinely encountered experiences and storing them as semantic memories. This preregistered study tested the hypothesis that caregiving-related early adversities (crEAs) shape affective semantic memories to reflect the content of those adverse interpersonal-affective experiences. We also tested the hypothesis that because affective semantic memories may continue to evolve in response to later-occurring positive experiences, child-perceived attachment security will inform their content. The sample comprised 160 children (ages 6-12 at Visit 1; 87F/73 M), 66% of whom experienced crEAs (n = 105). At Visit 1, crEA exposure prior to study enrollment was operationalized as parental-reports endorsing a history of crEAs (abuse/neglect, permanent/significant parent-child separation); while child-reports assessed concurrent attachment security. A false memory task was administered online â¼2.5 years later (Visit 2) to probe the content of affective semantic memories-specifically attachment schemas. Results showed that crEA exposure (vs. no exposure) was associated with a higher likelihood of falsely endorsing insecure (vs. secure) schema scenes. Attachment security moderated the association between crEA exposure and insecure schema-based false recognition. Findings suggest that interpersonal-affective semantic schemas include representations of parent-child interactions that may capture the quality of one's own attachment experiences and that these representations shape how children remember attachment-relevant narrative events. Findings are also consistent with the hypothesis that these affective semantic memories can be modified by later experiences. Moving forward, the approach taken in this study provides a means of operationalizing Bowlby's notion of internal working models within a cognitive neuroscience framework. RESEARCH HIGHLIGHTS: Affective semantic memories representing insecure schema knowledge (child needs + needs-not-met) may be more salient, elaborated, and persistent among youths exposed to early caregiving adversity. All youths, irrespective of early caregiving adversity exposure, may possess affective semantic memories that represent knowledge of secure schemas (child needs + needs-met). Establishing secure relationships with parents following early-occurring caregiving adversity may attenuate the expression of insecure semantic memories, suggesting potential malleability. Affective semantic memories include schema representations of parent-child interactions that may capture the quality of one's own attachment experiences and shape how youths remember attachment-relevant events.
ABSTRACT
Importance: Few investigations have evaluated rates of brain-based magnetic resonance imaging (MRI) incidental findings (IFs) in large lifespan samples, their stability over time, or their associations with health outcomes. Objectives: To examine rates of brain-based IFs across the lifespan, their persistence, and their associations with phenotypic indicators of behavior, cognition, and health; to compare quantified motion with radiologist-reported motion and evaluate its associations with IF rates; and to explore IF consistency across multiple visits. Design, Setting, and Participants: This cross-sectional study included participants from the Nathan Kline Institute-Rockland Sample (NKI-RS), a lifespan community-ascertained sample, and the Healthy Brain Network (HBN), a cross-sectional community self-referred pediatric sample focused on mental health and learning disorders. The NKI-RS enrolled participants (ages 6-85 years) between March 2012 and March 2020 and had longitudinal participants followed up for as long as 4 years. The HBN enrolled participants (ages 5-21 years) between August 2015 and October 2021. Clinical neuroradiology MRI reports were coded for radiologist-reported motion as well as presence, type, and clinical urgency (category 1, no abnormal findings; 2, no referral recommended; 3, consider referral; and 4, immediate referral) of IFs. MRI reports were coded from June to October 2021. Data were analyzed from November 2021 to February 2023. Main Outcomes and Measures: Rates and type of IFs by demographic characteristics, health phenotyping, and motion artifacts; longitudinal stability of IFs; and Euler number in projecting radiologist-reported motion. Results: A total of 1300 NKI-RS participants (781 [60.1%] female; mean [SD] age, 38.9 [21.8] years) and 2772 HBN participants (976 [35.2%] female; mean [SD] age, 10.0 [3.5] years) had health phenotyping and neuroradiology-reviewed MRI scans. IFs were common, with 284 of 2956 children (9.6%) and 608 of 1107 adults (54.9%) having IFs, but rarely of clinical concern (category 1: NKI-RS, 619 [47.6%]; HBN, 2561 [92.4%]; category 2: NKI-RS, 647 [49.8%]; HBN, 178 [6.4%]; category 3: NKI-RS, 79 [6.1%]; HBN, 30 [1.1%]; category 4: NKI-RS: 12 [0.9%]; HBN, 6 [0.2%]). Overall, 46 children (1.6%) and 79 adults (7.1%) required referral for their IFs. IF frequency increased with age. Elevated blood pressure and BMI were associated with increased T2 hyperintensities and age-related cortical atrophy. Radiologist-reported motion aligned with Euler-quantified motion, but neither were associated with IF rates. Conclusions and Relevance: In this cross-sectional study, IFs were common, particularly with increasing age, although rarely clinically significant. While T2 hyperintensity and age-related cortical atrophy were associated with BMI and blood pressure, IFs were not associated with other behavioral, cognitive, and health phenotyping. Motion may not limit clinical IF detection.
Subject(s)
Brain , Incidental Findings , Adult , Female , Humans , Child , Male , Cross-Sectional Studies , Brain/diagnostic imaging , Atrophy , Magnetic Resonance ImagingABSTRACT
Brain age, a measure of biological aging in the brain, has been linked to psychiatric illness, principally in adult populations. Components of socioeconomic status (SES) associate with differences in brain structure and psychiatric risk across the lifespan. This study aimed to investigate the influence of SES on brain aging in childhood and adolescence, a period of rapid neurodevelopment and peak onset for many psychiatric disorders. We reanalyzed data from the Healthy Brain Network to examine the influence of SES components (occupational prestige, public assistance enrollment, parent education, and household income-to-needs ratio [INR]) on relative brain age (RBA). Analyses included 470 youth (5-17 years; 61.3% men), self-identifying as White (55%), African American (15%), Hispanic (9%), or multiracial (17.2%). Household income was 3.95 ± 2.33 (mean ± SD) times the federal poverty threshold. RBA quantified differences between chronological age and brain age using covariation patterns of morphological features and total volumes. We also examined associations between RBA and psychiatric symptoms (Child Behavior Checklist [CBCL]). Models covaried for sex, scan location, and parent psychiatric diagnoses. In a linear regression, lower RBA is associated with lower parent occupational prestige (p = .01), lower public assistance enrollment (p = .03), and more parent psychiatric diagnoses (p = .01), but not parent education or INR. Lower parent occupational prestige (p = .02) and lower RBA (p = .04) are associated with higher CBCL anxious/depressed scores. Our findings underscore the importance of including SES components in developmental brain research. Delayed brain aging may represent a potential biological pathway from SES to psychiatric risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Subject(s)
Depression , Social Class , Male , Child , Adult , Humans , Adolescent , Female , Brain , Poverty , AnxietyABSTRACT
Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.
Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Connectome , Humans , Autistic Disorder/diagnostic imaging , Connectome/methods , Brain , Magnetic Resonance Imaging/methods , Brain Mapping/methodsABSTRACT
Data aggregation in mental health is complicated by using different questionnaires, and little is known about the impact of item harmonization strategies on measurement precision. Therefore, we aimed to assess the impact of various item harmonization strategies for a target and proxy questionnaire using correlated and bifactor models. Data were obtained from the Brazilian High-Risk Study for Mental Conditions (BHRCS) and the Healthy Brain Network (HBN; N = 6,140, ages 5-22 years, 39.6% females). We tested six item-wise harmonization strategies and compared them based on several indices. The one-by-one (1:1) expert-based semantic item harmonization presented the best strategy as it was the only that resulted in scalar-invariant models for both samples and factor models. The between-questionnaires factor correlation, reliability, and factor score difference in using a proxy instead of a target measure improved little when all other harmonization strategies were compared with a completely at-random strategy. However, for bifactor models, between-questionnaire specific factor correlation increased from 0.05-0.19 (random item harmonization) to 0.43-0.60 (expert-based 1:1 semantic harmonization) in BHRCS and HBN samples, respectively. Therefore, item harmonization strategies are relevant for specific factors from bifactor models and had little impact on p-factors and first-order correlated factors when the child behavior checklist (CBCL) and strengths and difficulties questionnaire (SDQ) were harmonized.
Subject(s)
Mental Disorders , Psychopathology , Child , Female , Humans , Adolescent , Male , Reproducibility of Results , Psychometrics , Mental Health , Surveys and Questionnaires , Mental Disorders/diagnosis , Mental Disorders/psychologyABSTRACT
BACKGROUND: Semi-structured diagnostic interviews and symptom checklists present similar internal reliability. We aim to investigate whether they differ in predicting poor life outcomes in the transition from childhood to young adulthood. METHODS: For this longitudinal study, we used data from the Brazilian High Risk Cohort Study for Childhood Mental Health Conditions. Eligible participants were aged 6-14 years on the day of study enrolment (January to February, 2010) and were enrolled in public schools by a biological parent in Porto Alegre and São Paulo, Brazil. 2511 young people and their caregivers were assessed at baseline in 2010-11, and 1917 were assessed 8 years later (2018-19; 76·3% retention). Clinical thresholds were derived using semi-structured parent-report interview based on the Diagnostic and Statistical Manual of Mental Disorders, according to the Developmental and Well-being Assessment (DAWBA), and clinical scores as defined by the Child Behavior Checklist (CBCL; T-score ≥70 considered positive caseness). At 8 years, participants were assessed for a composite life-threatening outcome (a composite of death, suicide attempts, severe self-harm, psychiatric inpatient admission, or emergency department visits) and a composite poor life chances outcome (a composite of any criminal conviction, substance misuse, or school dropout). We evaluated the accuracy of DAWBA and CBCL to predict these outcomes. Logistic regression models were adjusted for age, sex, race or ethnicity, study site, and socioeconomic class. FINDINGS: DAWBA and CBCL had similar sensitivity, specificity, predictive values, and test accuracy for both composite outcomes and their components. Any mental health problem, as classified by DAWBA and CBCL, was independently associated with the composite life-threatening outcome (DAWBA adjusted odds ratio 1·62, 95% CI 1·20-2·18; CBCL 1·66, 1·19-2·30), but only CBCL independently predicted poor life chances (1·56, 1·19-2·04). Participants classified by both approaches did not have higher odds of the life-threatening outcome when compared with participants classified by DAWBA or CBCL alone, nor for the poor life chances outcome when compared with those classified by CBCL alone. INTERPRETATION: Classifying children and adolescents based on a semi-structured diagnostic interview was not statistically different to symptom checklist in terms of test accuracy and predictive validity for relevant life outcomes. Classification based on symptom checklist might be a valid alternative to costly and time-consuming methods to identify young people at risk for poor life outcomes. FUNDING: Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; and Medical Research Council, European Research Council. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.
Subject(s)
Checklist , Mental Health , Adolescent , Humans , Child , Young Adult , Adult , Cohort Studies , Brazil , Longitudinal Studies , Reproducibility of ResultsABSTRACT
OBJECTIVE: The authors examined recent trends in incidence of psychotic disorders, demographic characteristics, and comorbid psychiatric and medical conditions among six racial/ethnic groups. METHOD: A retrospective cohort study design was used to examine the incidence of psychotic disorders across race/ethnicity groups and comorbid psychiatric and medical conditions among members of Kaiser Permanente Northern California from 2009 to 2019 (N=5,994,758). Poisson regression was used to assess changes in annual incidence, and Cox proportional hazards and logistic regression models adjusted for age and sex were used to test correlates and consequences. RESULTS: Overall, the incidence of nonaffective psychotic disorders decreased slightly over the study period. Compared with White members, the risk of nonaffective psychosis diagnosis was higher among Black (hazard ratio=2.13, 95% CI=2.02-2.24) and American Indian or Alaskan Native (AIAN) (hazard ratio=1.85, 95% CI=1.53-2.23) members and lower among Asian (hazard ratio=0.72, 95% CI=0.68-0.76) and Hispanic (hazard ratio=0.91, 95% CI=0.87-0.96) members, as well as those whose race/ethnicity was categorized as "other" (hazard ratio=0.92, 95% CI=0.86-0.99). Compared with White members, the risk of affective psychosis diagnosis adjusted for age and sex was higher among Black (hazard ratio=1.76, 95% CI=1.62-1.91), Hispanic (hazard ratio=1.09, 95% CI=1.02-1.16), and AIAN (hazard ratio=1.38, 95% CI=1.00-1.90) members and lower among Asian (hazard ratio=0.77, 95% CI=0.71-0.83), Native Hawaiian or other Pacific Islander (hazard ratio=0.69, 95% CI=0.48-0.99), and "other" (hazard ratio=0.86, 95% CI=0.77-0.96) members. Psychotic disorders were associated with significantly higher odds of suicide (odds ratio=2.65, 95% CI=2.15-3.28), premature death (odds ratio=1.30, 95% CI=1.22-1.39), and stroke (odds ratio=1.64, 95% CI=1.55-1.72) and lower odds of health care utilization (odds ratio=0.44, 95% CI=0.42-0.47). CONCLUSIONS: This study demonstrates racial and ethnic variation in incident psychotic disorder diagnoses in the United States, compared with non-Hispanic Whites. Individuals diagnosed with psychosis face a greater burden of other negative health outcomes and lower odds of health care utilization, reflecting personal and economic impacts. Identifying risk factors for elevated rates and protective influences in subgroups can inform strategies for prevention and interventions to ameliorate severe consequences of psychotic syndromes.
Subject(s)
Ethnicity , Psychotic Disorders , Humans , Incidence , Psychotic Disorders/diagnosis , Psychotic Disorders/ethnology , Retrospective Studies , United States , Racial GroupsABSTRACT
Importance: Limited systematic information on familial factors and perception of the benefits and harms of internet use by youths is available. Much of the current research has been hampered by small nondiverse samples and limited information on key familial and offspring characteristics. Objective: To characterize parental perceptions and concerns about internet use associated with adolescent development, well-being, safety, family connectedness, and potential for problematic internet use. Design, Setting, and Participants: A 20-minute, English-language survey was developed with expert stakeholders using previously validated questionnaires and was conducted online between June 17 and July 5, 2022. Participants included 1005 parents of children and adolescents aged 9 to 15 years drawn from an online digital survey platform and calibrated for representation with post hoc weightings. Main Outcomes and Measures: Parent survey responses about family characteristics and internet use were used to compute Internet Addiction Test scores for parents and their offspring, Alabama Parenting Questionnaire scores, and an aggregate family connectedness score. Results: The survey cohort of 1005 parents included 568 women (56.5%) and 437 men (43.5%) with a mean age (SD) of 39.5 (6.4) years. In terms of race and ethnicity, the most common categories included Black or African American (95 [9.5%]), Latinx or Hispanic (100 [10.0%]), White (602 [59.9%]), and 2 or more races or ethnicities (122 [12.1%]). Respondents endorsed parental concerns that included exposure to harmful content (646 [64.3%]) and online bullying (533 [53.0%]). Two hundred twenty-five parents (22.4%) had specific concerns about internet addiction in their adolescent offspring, and twice as many parents reported specific concerns about internet addiction than substance addiction. However, parents also indicated that internet use improved family connectedness among immediate families (468 [46.6%]) and extended families (568 [56.5%]). Internet Addiction Test scores in adolescent offspring were correlated with parent scores (ß = 0.62 [SE = 0.02]; P < .001) and Alabama Parenting Questionnaire-Inconsistent Discipline scores (ß = 0.23 [SE = 0.11]; P = .04). Conclusions and Relevance: In this survey study of parent perceptions of internet use among adolescent offspring, parents believed the internet brought families closer yet also expressed concerns. Problematic internet use among youths was correlated with negative parenting styles and parent internet use. This research adds to the literature by suggesting that families, their communities, and industry may have common ground to collaborate on reducing the negative effects of internet use.
Subject(s)
Internet Use , Parents , Adolescent , Adult , Child , Female , Humans , Male , Ethnicity , ParentingABSTRACT
Recent theories of cortical organisation suggest features of function emerge from the spatial arrangement of brain regions. For example, association cortex is located furthest from systems involved in action and perception. Association cortex is also 'interdigitated' with adjacent regions having different patterns of functional connectivity. It is assumed that topographic properties, such as distance between regions, constrains their functions, however, we lack a formal description of how this occurs. Here we use variograms, a quantification of spatial autocorrelation, to profile how function changes with the distance between cortical regions. We find function changes with distance more gradually within sensory-motor cortex than association cortex. Importantly, systems within the same type of cortex (e.g., fronto-parietal and default mode networks) have similar profiles. Primary and association cortex, therefore, are differentiated by how function changes over space, emphasising the value of topographical features of a region when estimating its contribution to cognition and behaviour.
Subject(s)
Cognition , Sensorimotor Cortex , Spatial AnalysisABSTRACT
Health and well-being are impacted by our thoughts and the things we do. In the laboratory, studies suggest specific task contexts impact thought processes. More broadly, this suggests the people we are with, the places we are in, and the activities we perform may influence our thought patterns. In our study, participants completed experience sampling surveys for five days in daily life. Principal component analysis decomposed this data to identify common "patterns of thought," and linear mixed modelling related these patterns to the participants' activities. Our study replicated the influence of socializing on patterns of thought and established that this is part of a broader set of relationships linking activities to how thoughts are organized in daily life. Our study suggests sampling thinking in the real world may help map thoughts to activities, and these "thought-activity" mappings could be useful to researchers and health care professionals interested in health and well-being.
Subject(s)
Ecological Momentary Assessment , Mental Processes , Humans , Principal Component Analysis , Social BehaviorABSTRACT
In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.
Subject(s)
Magnetic Resonance Imaging , Neuroimaging , Adult , Humans , Middle Aged , Young Adult , Brain/diagnostic imaging , Electrocardiography , ElectroencephalographyABSTRACT
Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem becomes more acute. Software that operates on imaging data defined using the Brain Imaging Data Structure (BIDS) - BIDS Apps - have provided a substantial advance. However, even using BIDS Apps, a full audit trail of data processing is a necessary prerequisite for fully reproducible research. Obtaining a faithful record of the audit trail is challenging - especially for large datasets. Recently, the FAIRly big framework was introduced as a way to facilitate reproducible processing of large-scale data by leveraging DataLad - a version control system for data management. However, the current implementation of this framework was more of a proof of concept, and could not be immediately reused by other investigators for different use cases. Here we introduce the BIDS App Bootstrap (BABS), a user-friendly and generalizable Python package for reproducible image processing at scale. BABS facilitates the reproducible application of BIDS Apps to large-scale datasets. Leveraging DataLad and the FAIRly big framework, BABS tracks the full audit trail of data processing in a scalable way by automatically preparing all scripts necessary for data processing and version tracking on high performance computing (HPC) systems. Currently, BABS supports jobs submissions and audits on Sun Grid Engine (SGE) and Slurm HPCs with a parsimonious set of programs. To demonstrate its scalability, we applied BABS to data from the Healthy Brain Network (HBN; n=2,565). Taken together, BABS allows reproducible and scalable image processing and is broadly extensible via an open-source development model.