Parental Deprivation- and Threat-Based Factors Associated with Youth Emotion-Based Neurocircuitry and Externalizing Behavior: A Systematic Review

Parental factors, including negative parenting practices (e.g., family conflict, low monitoring), parental depression, and parental substance use, are associated with externalizing behaviors among youth. However, the ways in which these parental factors are associated with youth brain function and consequent externalizing behavior has been less studied. Both the dimensional and stress acceleration models provide frameworks for understanding how parental factors may be associated with frontolimbic and frontoparietal networks implicated in emotional attention and regulation processes. The current review builds upon this work by examining how deprivation- and threat-based parental factors are associated with youth neurocircuitry involved in emotional functioning and externalizing behaviors. A systematic review using PRISMA guidelines was completed and included five studies assessing parenting behaviors, six studies assessing parental depressive symptoms and/or diagnosis, and 12 studies assessing parental history of substance use. Synthesis of reviewed studies discusses support for the dimensional and stress acceleration models within the context of deprivation and threat. Further, a limited number of studies tested (i.e., six studies) and supported (i.e., three studies) youth neural structure and function as a mediator of the association between parental factors and youth externalizing behavior. Specific recommendations for future work include more deliberate planning related to sample composition, improved clarity related to parental constructs, consistency in methodology, and longitudinal study design in order to better understand associations between contextual parental influences and youth neural and behavioral functioning.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Methods for decoding cortical gradients of functional connectivity

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity

The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.

Profiles of acculturative strategies and cultural stressors among Hispanic/Latinx college-attending emerging adults

OBJECTIVE

The present study identified unique profiles of cultural stressors (i.e., bicultural stress, discrimination, and negative context of reception) and acculturative strategies (i.e., heritage practices, heritage identification, U.S. practices, and U.S. identification), in Hispanic/Latinx (HL) emerging adults. Additionally, we examined associations between positive and negative psychosocial functioning, with profiles of acculturative strategies and cultural stressors.

METHOD

The present study utilized a baseline sample of 779 HL college students (75.8% female, Mage = 20.80 years, SD = 2.66) drawn from a daily diary study on acculturation.

RESULTS

Latent profile analysis identified four distinct profiles. The Bicultural and Low Cultural Stressors (B-LowCS; 53.55%) was marked by strong heritage and U.S. cultural orientation and low levels across all cultural stressors. The Marginalization and High Acculturative Stressors (M-HighAS; 20.13%) was marked by weak heritage and U.S. cultural orientation, high acculturative stressors, and low discrimination. The third profile, the Heritage Rejection and Low Cultural Stressors (HR-LowCS; 16.05%) was marked by rejection of heritage culture and low cultural stressors. Finally, the Separation and High Cultural Stressors (S-HighCS; 10.26%) was marked by weak U.S. cultural orientation and high cultural stressors. Consistent with past research, the B-LowCS profile was marked by the highest level of positive psychosocial functioning and the lowest levels of internalizing and externalizing symptoms.

CONCLUSIONS

The results of the present study highlight the usefulness of person-centered approaches for understanding the interplay between acculturative strategies and cultural stressors, and the implications of these distinct profiles on psychosocial functioning in HL emerging adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Acculturative Orientations Among Hispanic/Latinx Caregivers in the ABCD Study: Associations With Caregiver and Youth Mental Health and Youth Brain Function

Background

Population-based neuroscience offers opportunities to examine important but understudied sociocultural factors such as acculturation. Acculturation refers to the extent to which an individual retains their cultural heritage and/or adopts the receiving society's culture and is particularly salient among Hispanic/Latinx immigrants. Specific acculturative orientations have been linked to vulnerability to substance use, depression, and suicide and are known to influence family dynamics between caregivers and their children.

Methods

Using data from first- and second-generation Hispanic/Latinx caregivers in the Adolescent Brain Cognitive Development (ABCD) Study (N = 1057), we examined how caregivers' acculturative orientation affects their mental health, as well as the mental health and brain function of their children. Neuroimaging analyses focused on regions associated with self- and affiliation-based social processing (ventromedial prefrontal cortex, insula, and temporoparietal junction).

Results

We identified 2 profiles of caregiver acculturation: bicultural (retains heritage culture while adopting U.S. culture) and detached (discards heritage culture and rejects U.S. culture). Bicultural caregivers exhibited fewer internalizing and externalizing problems than detached caregivers; furthermore, youth exhibited similar internalizing effects across caregiver profiles. In addition, youth with bicultural caregivers displayed increased resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations and regional homogeneity) in the left insula, which has been linked to psychopathology; however, differences in long-range functional connectivity were not significant.

Conclusions

Caregiver acculturation is an important familial factor that has been linked to significant differences in youth mental health and insula activity. Future work should examine sociocultural and neurodevelopmental changes across adolescence to assess health outcomes and determine whether localized, corticolimbic brain effects are ultimately translated into long-range connectivity differences.

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Profiling intra- and inter-individual differences in brain development across early adolescence

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

Convergent abnormality in the subgenual anterior cingulate cortex in insomnia disorder: A revisited neuroimaging meta-analysis of 39 studies

The neurobiological underpinnings of insomnia disorder (ID) are still poorly understood. A previous meta-analysis conducted by our research group in 2018 revealed no consistent regional alterations based on the limited number of eligible studies. Given the number of studies published during the last few years, we revisited the meta-analysis to provide an update to the field. Following the best-practice guidelines for conducting neuroimaging meta-analyses, we searched several databases (PubMed, Web of Science, and BrainMap) and identified 39 eligible structural and functional studies, reporting coordinates reflecting significant group differences between ID patients and healthy controls. A significant convergent regional alteration in the subgenual anterior cingulate cortex (sgACC) was observed using the activation likelihood estimation algorithm. Behavioural decoding using the BrainMap database indicated that this region is involved in fear-related emotional and cognitive processing. The sgACC showed robust task-based co-activation in meta-analytic connectivity modelling and task-free functional connectivity in a resting-state functional connectivity analysis with the main hubs of the salience and default mode networks, including the posterior cingulate cortex and dorsal ACC, amygdala, hippocampus, and medial prefrontal cortex. Collectively, the findings from this large-scale meta-analysis suggest a critical role of the sgACC in the pathophysiology of ID.

Task-based attentional and default mode connectivity associated with science and math anxiety profiles among university physics students

PURPOSE

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students.

PROCEDURES

Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task.

FINDINGS

No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity.

CONCLUSIONS

These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.

Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design

Importance

The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or "Long COVID") in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.

Observations

We describe the protocol for the Pediatric Observational Cohort Study of the NIH's RE searching COV ID to E nhance R ecovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of five cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study ( n =10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n=6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n=6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n=600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science.

Conclusions and Relevance

RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions.

Clinical Trialsgov Identifier

Clinical Trial Registration: http://www.clinicaltrials.gov . Unique identifier: NCT05172011.

Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity

The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.

The Link Between Neuroticism and Everyday Cognitive Failures is Mediated by Self-Reported Mindfulness Among College Students

Neuroticism has been linked to an increased likelihood of cognitive failures, including episodes of inattentiveness, forgetfulness, or accidents causing difficulties in successfully executing everyday tasks and impacting health and quality of life. Cognitive failures associated with trait neuroticism can prompt some negative psychological outcomes and risky behaviors. Accumulating evidence shows that augmenting mindfulness can benefit cognitive health and general well-being. However, little is known regarding potential cognitive-behavioral pathways through which individual differences in trait neuroticism could influence the propensity to cognitive failures. Using a sample of 1003 undergraduate college students (females: n = 779) consisting of self-reported questionnaire data, we conducted correlational and mediational analyses to investigate the interrelationship between neuroticism, mindfulness, and cognitive failures. Higher neuroticism scores (females: r = -0.388, males: r = -0.390) and higher cognitive failures scores (females: r = -0.339, males: r = -0.407, p < .001) were significantly correlated with lower self-reported mindfulness scores. Mindfulness significantly mediated the relationship between neuroticism and cognitive failures (β = 0.50, 95%, CI: 0.37, 0.65). These findings indicate that higher mindfulness may help ameliorate negative effects of neuroticism on everyday cognitive failures. Future research will determine how college students may benefit from positive impact of mindfulness to improve their psychological and physical health.

Neural systems underlying RDoC social constructs: An activation likelihood estimation meta-analysis

Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH's Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the "social brain". We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations.

The association of amygdala-insula functional connectivity and adolescent e-cigarette use via sleep problems and depressive symptoms

BACKGROUND

Adolescent electronic cigarette (e-cigarette) use remains high. Elucidating contributing factors may enhance prevention strategies. Neurobiologically, amygdala-insula resting-state functional connectivity (rsFC) has been linked with aspects of sleep, affect, and substance use (SU). As such, we hypothesized that amygdala's rsFC with the insula would be associated with e-cigarette use via sleep problems and/or depression levels.

METHODS

An adolescent sample (N = 146) completed a rs-fMRI scan at time 1 and self-reports at time 2 (∼15 months later). Given consistent associations between mental health outcomes and the rsFC of the laterobasal amygdala (lbAMY) with the anterior insula, we utilized a seed region (lbAMY) to region of interest (ROI) analysis approach to characterize brain-behavior relationships. Two serial mediation models tested the interrelations between amygdala's rsFC with distinct anterior insula subregions (i.e., ventral insula [vI], dorsal insula [dI]), sleep problems, depression levels, and days of e-cigarette use.

RESULTS

An indirect effect was observed when considering the lbAMY's rsFC with the vI. Greater rsFC predicted more sleep problems, more sleep problems were linked with greater depressive symptoms, and greater depressive symptoms were associated with more e-cigarette use (indirect effect = 0.08, CI [0.01,0.21]). Indicative of a neurobiological dissociation, a similar indirect effect linking these variables was not observed when considering the lbAMY's rsFC with the dI (indirect effect = 0.03, CI [-0.001,0.10]).

CONCLUSIONS

These outcomes highlight functional interactions between the amygdala and insula as a neurobiological contributor to sleep problems, depressive symptoms, and ultimately SU thereby suggesting potential intervention points to reduce teen e-cigarette use.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BACKGROUND

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

Extended functional connectivity of convergent structural alterations among individuals with PTSD: a neuroimaging meta-analysis

Background

Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated.

Methods

Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations.

Results

We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes.

Conclusions

Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12993-022-00196-2.

Sleep to Internalizing Pathway in Young Adolescents (SIPYA): A proposed neurodevelopmental model

The prevalence of internalizing disorders, i.e., anxiety and depressive disorders, spikes in adolescence and has been increasing amongst adolescents despite the existence of evidence-based treatments, highlighting the need for advancing theories on how internalizing disorders emerge. The current review presents a theoretical model, called the Sleep to Internalizing Pathway in Young Adolescents (SIPYA) Model, to explain how risk factors, namely sleep-related problems (SRPs), are prospectively associated with internalizing disorders in adolescence. Specifically, SRPs during late childhood and early adolescence, around the initiation of pubertal development, contribute to the interruption of intrinsic brain networks dynamics, both within the default mode network and between the default mode network and other networks in the brain. This interruption leaves adolescents vulnerable to repetitive negative thought, such as worry or rumination, which then increases vulnerability to internalizing symptoms and disorders later in adolescence. Sleep-related behaviors are observable, modifiable, low-stigma, and beneficial beyond treating internalizing psychopathology, highlighting the intervention potential associated with understanding the neurodevelopmental impact of SRPs around the transition to adolescence. This review details support for the SIPYA Model, as well as gaps in the literature and future directions.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Risky decision-making strategies mediate the relationship between amygdala activity and real-world financial savings among individuals from lower income households: A pilot study

Lower financial savings among individuals experiencing adverse social determinants of health (SDoH) increases vulnerabilities during times of crisis. SDoH including low socioeconomic status (low-SES) influence cognitive abilities as well as health and life outcomes that may perpetuate poverty and disparities. Despite evidence suggesting a role for financial growth in minimizing SDoH-related disparities and vulnerabilities, neurobiological mechanisms linked with financial behavior remain to be elucidated. As such, we examined the relationships between brain activity during decision-making (DM), laboratory-based task performance, and money savings behavior. Participants (N = 24, 14 females) from low-SES households (income<$20,000/year) underwent fMRI scanning while performing the Balloon Analogue Risk Task (BART), a DM paradigm probing risky- and strategic-DM processes. Participants also completed self-report instruments characterizing relevant personality characteristics and then engaged in a community outreach financial program where amount of money saved was tracked over a 6-month period. Regarding BART-related brain activity, we observed expected activity in regions implicated in reward and emotional processing including the amygdala. Regarding brain-behavior relationships, we found that laboratory-based BART performance mediated the impact of amygdala activity on real-world behavior. That is, elevated amygdala activity was linked with BART strategic-DM which, in turn, was linked with more money saved after 6 months. In exploratory analyses, this mediation was moderated by emotion-related personality characteristics such that, only individuals reporting lower alexithymia demonstrated a relationship between amygdala activity and savings. These outcomes suggest that DM-related amygdala activity and/or emotion-related personality characteristics may provide utility as an endophenotypic marker of individual's financial savings behavior.

Convergent regional brain abnormalities in behavioral variant frontotemporal dementia: A neuroimaging meta-analysis of 73 studies

Introduction

Numerous studies have reported brain alterations in behavioral variant frontotemporal dementia (bvFTD). However, they pointed to inconsistent findings.

Methods

We used a meta‐analytic approach to identify the convergent structural and functional brain abnormalities in bvFTD. Following current best‐practice neuroimaging meta‐analysis guidelines, we searched PubMed and Embase databases and performed reference tracking. Then, the coordinates of group comparisons between bvFTD and controls from 73 studies were extracted and tested for convergence using activation likelihood estimation.

Results

We identified convergent abnormalities in the anterior cingulate cortices, anterior insula, amygdala, paracingulate, striatum, and hippocampus. Task‐based and resting‐state functional connectivity pointed to the networks that are connected to the obtained consistent regions. Functional decoding analyses suggested associated dysfunction of emotional processing, interoception, reward processing, higher‐order cognitive functions, and olfactory and gustatory perceptions in bvFTD.

Discussion

Our findings highlighted the key role of the salience network and subcortical regions in the pathophysiology of bvFTD.

HIV infection is linked with reduced error-related default mode network suppression and poorer medication management abilities

OBJECTIVE

Brain activity linked with error processing has rarely been examined among persons living with HIV (PLWH) despite importance for monitoring and modifying behaviors that could lead to adverse health outcomes (e.g., medication non-adherence, drug use, risky sexual practices). Given that cannabis (CB) use is prevalent among PLWH and impacts error processing, we assessed the influence of HIV serostatus and chronic CB use on error-related brain activity while also considering associated implications for everyday functioning and clinically-relevant disease management behaviors.

METHODS

A sample of 109 participants, stratified into four groups by HIV and CB (HIV+/CB+, n = 32; HIV+/CB-, n = 27; HIV-/CB+, n = 28; HIV-/CB-, n = 22), underwent fMRI scanning while completing a modified Go/NoGo paradigm called the Error Awareness Task (EAT). Participants also completed a battery of well-validated instruments including a subjective report of everyday cognitive failures and an objective measure of medication management abilities.

RESULTS

Across all participants, we observed expected error-related anterior insula (aI) activation which correlated with better task performance (i.e., less errors) and, among HIV- participants, fewer self-reported cognitive failures. Regarding awareness, greater insula activation as well as greater posterior cingulate cortex (PCC) deactivation were notably linked with aware (vs. unaware) errors. Regarding group effects, unlike HIV- participants, PLWH displayed a lack of error-related deactivation in two default mode network (DMN) regions (i.e., PCC, medial prefrontal cortex [mPFC]). No CB main or interaction effects were detected. Across all participants, reduced error-related PCC deactivation correlated with reduced medication management abilities and PCC deactivation mediated the effect of HIV on such abilities. More lifetime CB use was linked with reduced error-related mPFC deactivation among HIV- participants and poorer medication management across CB users.

CONCLUSIONS

These results demonstrate that insufficient error-related DMN suppression linked with HIV infection, as well as chronic CB use among HIV- participants, has real-world consequences for medication management behaviors. We speculate that insufficient DMN suppression may reflect an inability to disengage task irrelevant mental operations, ultimately hindering error monitoring and behavior modification.

The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug and natural reward-related stimuli

The cue-reactivity paradigm is a widely adopted neuroimaging probe engendering brain activity linked with attentional, affective, and reward processes following presentation of appetitive stimuli. Given the multiple mental operations invoked, we sought to decompose cue-related brain activity into constituent components employing emergent meta-analytic techniques when considering drug and natural reward-related cues. We conducted coordinate-based meta-analyses delineating common and distinct brain activity convergence across cue-reactivity studies (N = 196 articles) involving drug (n = 133) or natural (n = 63) visual stimuli. Across all studies, convergence was observed in limbic, cingulate, insula, and fronto-parieto-occipital regions. Drug-distinct convergence was observed in posterior cingulate, dorsolateral prefrontal, and temporo-parietal regions, whereas distinct-natural convergence was observed in thalamic, insular, orbitofrontal, and occipital regions. We characterized connectivity profiles of identified regions by leveraging task-independent and task-dependent MRI datasets, grouped these profiles into subnetworks, and linked each with putative mental operations. Outcomes suggest multifaceted brain activity during cue-reactivity can be decomposed into elemental processes and indicate that while drugs of abuse usurp the brain's natural-reward-processing system, some regions appear distinct to drug cue-reactivity.

Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study

BACKGROUND

The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12.

METHODS

This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD).

PRIMARY RESULTS

At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p's<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03).

CONCLUSIONS

ABCD Study participants aged 9-10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Baseline brain function in the preadolescents of the ABCD Study

The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.

Altered hippocampal microstructure and function in children who experienced Hurricane Irma

Hurricane Irma was the most powerful Atlantic hurricane in recorded history, displacing 6 million and killing over 120 people in the state of Florida alone. Unpredictable disasters like Irma are associated with poor cognitive and health outcomes that can disproportionately impact children. This study examined the effects of Hurricane Irma on the hippocampus and memory processes previously related to unpredictable stress. We used an innovative application of an advanced diffusion-weighted imaging technique, restriction spectrum imaging (RSI), to characterize hippocampal microstructure (i.e., cell density) in 9- to 10-year-old children who were exposed to Hurricane Irma relative to a non-exposed control group (i.e., assessed the year before Hurricane Irma). We tested the hypotheses that the experience of Hurricane Irma would be associated with decreases in: (a) hippocampal cellularity (e.g., neurogenesis), based on known associations between unpredictable stress and hippocampal alterations; and (b) hippocampal-related memory function as indexed by delayed recall. We show an association between decreased hippocampal cellularity and delayed recall memory in children who experienced Hurricane Irma relative to those who did not. These findings suggest an important role of RSI for assessing subtle microstructural changes related to functionally significant changes in the developing brain in response to environmental events.

Reward Processing in Children With Disruptive Behavior Disorders and Callous-Unemotional Traits in the ABCD Study

OBJECTIVE

Disrupted reward processing is implicated in the etiology of disruptive behavior disorders (DBDs) and callous-unemotional traits. However, neuroimaging investigations of reward processing underlying these phenotypes remain sparse. The authors examined neural sensitivity in response to reward anticipation and receipt among youths with DBDs, with and without callous-unemotional traits.

METHODS

Data were obtained from the Adolescent Brain and Cognitive Development Study (mean age=9.51 years [SD=0.50]; 49% female). Reward-related activation during the monetary incentive delay task was examined across 16 brain regions, including the amygdala, anterior cingulate cortex (ACC), nucleus accumbens (NAcc), and orbitofrontal cortex (OFC). Latent variable modeling was used to examine network-level coactivation. The following diagnostic groups were compared: typically developing youths (N=693) and youths with DBDs (N=995), subdivided into those with callous-unemotional traits (DBD+CU, N=198) and without callous-unemotional traits (DBD only, N=276).

RESULTS

During reward anticipation, youths in the overall DBD group (with and without callous-unemotional traits) showed decreased dorsal ACC activation compared with typically developing youths. The DBD-only group exhibited reduced ventral and dorsal striatal activity compared with the DBD+CU and typically developing groups. During reward receipt, youths with DBDs showed increased cortical (e.g., OFC) and subcortical (e.g., NAcc) regional activation compared with typically developing youths. The DBD+CU group demonstrated greater activation in several regions compared with those in the typically developing (e.g., amygdala) and DBD-only (e.g., dorsal ACC) groups. At the network level, the DBD-only group showed reduced anticipatory reward activation compared with the typically developing and DBD+CU groups, whereas youths in the DBD+CU group showed increased activation during reward receipt compared with those in the typically developing group.

CONCLUSIONS

These findings advance our understanding of unique neuroetiologic pathways to DBDs and callous-unemotional traits.

Correspondence Between Perceived Pubertal Development and Hormone Levels in 9-10 Year-Olds From the Adolescent Brain Cognitive Development Study

Aim

To examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.

Methods

Cross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.

Results

PDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.

Conclusions

Sociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

Estimating the prevalence of missing experiments in a neuroimaging meta-analysis

Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple functional magnetic resonance imaging experiments with the goal of obtaining results that are more likely to generalize. However, the interpretation of CBMA findings can be impaired by the file drawer problem, a type of publication bias that refers to experiments that are carried out but are not published. Using foci per contrast count data from the BrainMap database, we propose a zero-truncated modeling approach that allows us to estimate the prevalence of nonsignificant experiments. We validate our method with simulations and real coordinate data generated from the Human Connectome Project. Application of our method to the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing experiments estimated as at least 6 per 100 reported. The R code that we used is available at https://osf.io/ayhfv/.

Multiple large-scale neural networks underlying emotion regulation

Recent models suggest emotion generation, perception, and regulation rely on multiple, interacting large-scale brain networks. Despite the wealth of research in this field, the exact functional nature and different topological features of these neural networks remain elusive. Here, we addressed both using a well-established data-driven meta-analytic grouping approach. We applied k-means clustering to a large set of previously published experiments investigating emotion regulation (independent of strategy, goal and stimulus type) to segregate the results of these experiments into large-scale networks. To elucidate the functional nature of these distinct networks, we used functional decoding of metadata terms (i.e. task-level descriptions and behavioral domains). We identified four large-scale brain networks. The first two were related to regulation and functionally characterized by a stronger focus on response inhibition or executive control versus appraisal or language processing. In contrast, the second two networks were primarily related to emotion generation, appraisal, and physiological processes. We discuss how our findings corroborate and inform contemporary models of emotion regulation and thereby significantly add to the literature.

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Disruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study

BACKGROUND

Neurobiological differences linked to socioemotional and cognitive processing are well documented in youths with disruptive behavior disorders (DBDs), especially youths with callous-unemotional (CU) traits. The current study expanded this literature by examining gray matter volume (GMV) differences among youths with DBD with CU traits (DBDCU+), youths with DBD without CU traits (DBD-only), and youths that were typically developing (TD).

METHODS

Data were from the first full sample release of the Adolescent Brain and Cognitive Development Study (mean age = 9.49 years; 49% female). We tested whether the GMVs of 11 regions of interest selected a priori differentiated between our 3 groups: DBDCU+ (n = 288), DBD-only (n = 362), and TD (n = 915). Models accounted for demographic confounders, attention-deficit/hyperactivity disorder, and intracranial volume. We examined two potential moderators of the relationship between GMVs and group membership: sex and clinically significant anxiety (i.e., primary vs. secondary CU traits subtype).

RESULTS

Youths in the DBDCU+ group had lower right amygdala GMV, and youths in the DBD-only group had lower bilateral amygdala GMV relative to TD youths. Youths in the DBDCU+ group had lower bilateral hippocampal GMV, and youths in the DBD-only group had lower left hippocampal GMV relative to TD youths. Youths in the DBDCU+ group evidenced lower left insula GMV relative to TD youths. Finally, youths in the DBD-only group had lower left superior frontal gyrus and lower right caudal anterior cingulate cortex GMVs relative to TD youths. There was no moderation of associations between GMV and group membership by sex.

CONCLUSIONS

Our findings implicate structural aberrations in both the amygdala and hippocampus in the etiology of DBDs, with minimal evidence for differences based on the presence or absence of CU traits.

Ontological Dimensions of Cognitive-Neural Mappings

The growing literature reporting results of cognitive-neural mappings has increased calls for an adequate organizing ontology, or taxonomy, of these mappings. This enterprise is non-trivial, as relevant dimensions that might contribute to such an ontology are not yet agreed upon. We propose that any candidate dimensions should be evaluated on their ability to explain observed differences in functional neuroimaging activation patterns. In this study, we use a large sample of task-based functional magnetic resonance imaging (task-fMRI) results and a data-driven strategy to identify these dimensions. First, using a data-driven dimension reduction approach and multivariate distance matrix regression (MDMR), we quantify the variance among activation maps that is explained by existing ontological dimensions. We find that 'task paradigm' categories explain more variance among task-activation maps than other dimensions, including latent cognitive categories. Surprisingly, 'study ID', or the study from which each activation map was reported, explained close to 50% of the variance in activation patterns. Using a clustering approach that allows for overlapping clusters, we derived data-driven latent activation states, associated with re-occurring configurations of the canonical frontoparietal, salience, sensory-motor, and default mode network activation patterns. Importantly, with only four data-driven latent dimensions, one can explain greater variance among activation maps than all conventional ontological dimensions combined. These latent dimensions may inform a data-driven cognitive ontology, and suggest that current descriptions of cognitive processes and the tasks used to elicit them do not accurately reflect activation patterns commonly observed in the human brain.

Functional Characterization of Atrophy Patterns Related to Cognitive Impairment

Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions.

Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age.

Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age.

Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations.

Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient

The hippocampus displays a complex organization and function that is perturbed in many neuropathologies. Histological work revealed a complex arrangement of subfields along the medial-lateral and the ventral-dorsal dimension, which contrasts with the anterior-posterior functional differentiation. The variety of maps has raised the need for an integrative multimodal view. We applied connectivity-based parcellation to 1) intrinsic connectivity 2) task-based connectivity, and 3) structural covariance, as complementary windows into structural and functional differentiation of the hippocampus. Strikingly, while functional properties (i.e., intrinsic and task-based) revealed similar partitions dominated by an anterior-posterior organization, structural covariance exhibited a hybrid pattern reflecting both functional and cytoarchitectonic subdivision. Capitalizing on the consistency of functional parcellations, we defined robust functional maps at different levels of partitions, which are openly available for the scientific community. Our functional maps demonstrated a head-body and tail partition, subdivided along the anterior-posterior and medial-lateral axis. Behavioral profiling of these fine partitions based on activation data indicated an emotion-cognition gradient along the anterior-posterior axis and additionally suggested a self-world-centric gradient supporting the role of the hippocampus in the construction of abstract representations for spatial navigation and episodic memory.

Brain activity links performance in science reasoning with conceptual approach

Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning.

ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data

Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioral observation of symptomology (DSM-5/ICD-10) and may be prone to misdiagnosis. In order to move the field toward more quantitative diagnosis, we need advanced and scalable machine learning infrastructure that will allow us to identify reliable biomarkers of mental health disorders. In this paper, we propose a framework called ASD-DiagNet for classifying subjects with ASD from healthy subjects by using only fMRI data. We designed and implemented a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the model. Further, we designed and implemented a data augmentation strategy, based on linear interpolation on available feature vectors, that allows us to produce synthetic datasets needed for training of machine learning models. The proposed approach is evaluated on a public dataset provided by Autism Brain Imaging Data Exchange including 1, 035 subjects coming from 17 different brain imaging centers. Our machine learning model outperforms other state of the art methods from 10 imaging centers with increase in classification accuracy up to 28% with maximum accuracy of 82%. The machine learning technique presented in this paper, in addition to yielding better quality, gives enormous advantages in terms of execution time (40 min vs. 7 h on other methods). The implemented code is available as GPL license on GitHub portal of our lab (https://github.com/pcdslab/ASD-DiagNet).

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Sex differences in brain correlates of STEM anxiety

Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning.

Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder

The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes.

Author Correction: No evidence for a bilingual executive function advantage in the ABCD study

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Functional brain alterations in acute sleep deprivation: An activation likelihood estimation meta-analysis

Sleep deprivation (SD) is a common problem in modern societies, which leads to cognitive dysfunctions including attention lapses, impaired working memory, hindering decision making, impaired emotional processing, and motor vehicle accidents. Numerous neuroimaging studies have investigated the neural correlates of SD, but these studies have reported inconsistent results. Thus, we aimed to identify convergent patterns of abnormal brain functions due to acute SD. Based on the preferred reporting for systematic reviews and meta-analyses statement, we searched the PubMed database and performed reference tracking and finally retrieved 31 eligible functional neuroimaging studies. Then, we applied activation estimation likelihood meta-analysis and found reduced activity mainly in the right intraparietal sulcus and superior parietal lobule. The functional decoding analysis using the BrainMap database indicated that this region is mostly related to visuospatial perception, memory and reasoning. The significant co-activation of this region using the BrainMap database were found in the left superior parietal lobule, intraparietal sulcus, bilateral occipital cortex, left fusiform gyrus and thalamus. This region also connected with the superior parietal lobule, intraparietal sulcus, insula, inferior frontal gyrus, precentral, occipital and cerebellum through resting-state functional connectivity in healthy subjects. Taken together, our findings highlight the role of superior parietal cortex in SD.

Brain-based ranking of cognitive domains to predict schizophrenia

Schizophrenia is a devastating brain disorder that disturbs sensory perception, motor action, and abstract thought. Its clinical phenotype implies dysfunction of various mental domains, which has motivated a series of theories regarding the underlying pathophysiology. Aiming at a predictive benchmark of a catalog of cognitive functions, we developed a data-driven machine-learning strategy and provide a proof of principle in a multisite clinical dataset (n = 324). Existing neuroscientific knowledge on diverse cognitive domains was first condensed into neurotopographical maps. We then examined how the ensuing meta-analytic cognitive priors can distinguish patients and controls using brain morphology and intrinsic functional connectivity. Some affected cognitive domains supported well-studied directions of research on auditory evaluation and social cognition. However, rarely suspected cognitive domains also emerged as disease relevant, including self-oriented processing of bodily sensations in gustation and pain. Such algorithmic charting of the cognitive landscape can be used to make targeted recommendations for future mental health research.

No evidence for a bilingual executive function advantage in the nationally representative ABCD study

Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial1 findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-2-4 and large-sample5,6 studies have reported a bilingual executive function advantage (see refs. 7-9 for a review), there have been several failures to replicate these findings10-15, and recent meta-analyses have called into question the reliability of the original empirical claims8,9. Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals7,16,17. However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood18, we found little evidence that it engenders additional benefits to executive function development.

Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit

Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naïve Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs.

Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction

INTRODUCTION

About 30-40% of the population report sexual dysfunction. Although it is well known that the brain controls sexual behavior, little is known about the neural basis of sexual dysfunction.

AIM

To assess convergence of altered brain activity associated with sexual dysfunction across available functional imaging studies.

METHODS

We used activation likelihood estimation meta-analysis to quantify interstudy concordance across 14 functional imaging studies reporting 179 foci from 40 individual analyses involving 191 subjects with sexual dysfunction and 123 controls.

MAIN OUTCOME MEASURE

Activation likelihood estimation scores were used to assess convergence of findings.

RESULTS

Consistently decreased brain activity associated with sexual dysfunction was identified in the dorsal anterior cingulate cortex, ventral striatum, dorsal midbrain, anterior midcingulate cortex, and lateral orbitofrontal cortex.

CLINICAL IMPLICATION

These findings can serve as a basis for further studies on the pathophysiology of this highly common disorder with the view to development of more-specific treatment strategies.

STRENGTH & LIMITATIONS

Findings are based on an observer-independent meta-analysis that provides robust evidence for and anatomic localization of altered brain activity related to sexual dysfunction. Our analysis cannot distinguish between the putative sources of sexual dysfunction, but it provides a more ubiquitous and general pattern of related altered neural activity.

CONCLUSION

The identified regions have previously been shown to be critically involved in mediating sexual arousal and to be part of the sympathetic division of the autonomic nervous system. This suggests that the disturbance of brain activity associated with sexual dysfunction primarily affects sexual arousal already at early stages that are controlled by the sympathetic nervous system. Poeppl TB, Langguth B, Laird AR, et al. Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction. J Sex Med 2019;16:614-617.

Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results

Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior.

Meta-analytic evidence for a core problem solving network across multiple representational domains

Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development.