Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

Hubbard, Nicholas A.; Siless, Viviana; Frosch, Isabelle R.; Goncalves, Mathias; Lo, Nicole; Wang, J.; Bauer, Clemens; Conroy, Kathleen; Cosby, Elizabeth A.; Hay, Aleena C.; Jones, Rosanna; Pinaire, Megan; Souza, F. Vaz De; Vergara, Genesis A.; Ghosh, Satrajit; Henin, Aude; Hirshfeld‐Becker, Dina R.; Hofmann, Stefan G.; Rosso, Isabelle M.; Auerbach, Randy P.; Pizzagalli, Diego A.; Yendiki, Anastasia; Gabrieli, John D. E.; Whitfield-Gabrieli, Susan

doi:10.1016/j.nicl.2020.102240

Cited by 24 publications

(17 citation statements)

References 148 publications

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“…Adolescents aged 14–17 diagnosed with anxiety disorders (Anx = 41; mean age = 15.19) and matched healthy controls (HC = 55, mean age = 15.31) were enrolled in the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) project. Clinical characteristics, diagnostic criteria, and demographics information have been previously reported (see [ 27 , 28 ]). Sample clinical characteristics are summarized in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders

et al. 2020

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Adolescents with anxiety disorders exhibit excessive emotional and somatic arousal. Neuroimaging studies have shown abnormal cerebral cortical activation and connectivity in this patient population. The specific role of cerebellar output circuitry, specifically the dentate nuclei (DN), in adolescent anxiety disorders remains largely unexplored. Resting-state functional connectivity analyses have parcellated the DN, the major output nuclei of the cerebellum, into three functional territories (FTs) that include default-mode, salience-motor, and visual networks. The objective of this study was to understand whether FTs of the DN are implicated in adolescent anxiety disorders. Forty-one adolescents (mean age 15.19 ± 0.82, 26 females) with one or more anxiety disorders and 55 age- and gender-matched healthy controls completed resting-state fMRI scans and a self-report survey on anxiety symptoms. Seed-to-voxel functional connectivity analyses were performed using the FTs from DN parcellation. Brain connectivity metrics were then correlated with State-Trait Anxiety Inventory (STAI) measures within each group. Adolescents with an anxiety disorder showed significant hyperconnectivity between salience-motor DN FT and cerebral cortical salience-motor regions compared to controls. Salience-motor FT connectivity with cerebral cortical sensorimotor regions was significantly correlated with STAI-trait scores in HC (R2 = 0.41). Here, we report DN functional connectivity differences in adolescents diagnosed with anxiety, as well as in HC with variable degrees of anxiety traits. These observations highlight the relevance of DN as a potential clinical and sub-clinical marker of anxiety.

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Section: Methodsmentioning

confidence: 99%

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders

et al. 2020

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“…Given challenges inherent to neuroimaging research, particularly with clinical developmental samples, big data studies will be essential to continued progress in identifying neurodevelopmental trajectories associated with pediatric anxiety. A growing number of large cross-sectional or longitudinal neuroimaging studies of childhood and/or adolescence are available with measures related to anxiety ( Alexander et al, 2017 ; Casey et al, 2018 ; Evans, 2006 ; Hubbard et al, 2020 ; Jaddoe et al, 2006 ; Jernigan et al, 2016 ; Nooner et al, 2012 ; Pausova et al, 2017 ; Satterthwaite et al, 2016 ; Salum et al, 2015 ; Schumann et al, 2010 ; Somerville et al, 2018 ; Volkow et al, 2018 ). Each of these datasets contains measures of structural and/or functional neuroimaging, anxiety symptoms, and various other relevant measures in cognitive, emotional, social, behavioral, physical, and genetic domains ( Table 1 ).…”

Section: Examining Neurodevelopment and Pediatric Anxiety In Big Data Studiesmentioning

confidence: 99%

“…Given different study designs and data modalities, existing big data studies have complementary strengths and are poised to address distinct questions related to pediatric anxiety (for open questions well-suited to investigation with large datasets, see Table 2 ). For example, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is harmonized with the Human Connectome Project (HCP), has a uniquely large clinical sample with a focus on recruiting adolescents ages 14−17 (N = 225) with and without anxiety and depression ( Hubbard et al, 2020 ). The fMRI tasks in the BANDA study focus on processes with direct clinical relevance to anxiety (e.g., emotion processing, emotional interference), making it an ideal dataset for probing brain function in clinically anxious youth and parsing heterogeneity in anxious subtypes.…”

Section: Examining Neurodevelopment and Pediatric Anxiety In Big Data Studiesmentioning

confidence: 99%

“…Specifically, the BANDA study uses the Emotion Processing Task (EPT) to examine emotional reactivity, the Incentive Processing Task to probe responsiveness to reward, and the Emotion Interference Task to investigate cognitive control. From this research, longitudinal functional imaging data from the EPT, for example, can be used to test whether functional patterns of activation during emotional reactivity differentially predict changes in anxiety versus depressive symptomatology later in adolescence ( Hubbard et al, 2020 ). Taken together, these examples indicate some of the ways that large datasets can be used to delineate process-specific neurodevelopmental trajectories specific to and predictive of anxiety disorders.…”

Section: Examining Neurodevelopment and Pediatric Anxiety In Big Data Studiesmentioning

confidence: 99%

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Leveraging big data to map neurodevelopmental trajectories in pediatric anxiety

Zacharek

Kribakaran

Kitt

et al. 2021

Developmental Cognitive Neuroscience

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Anxiety disorders are the most prevalent psychiatric condition among youth, with symptoms commonly emerging prior to or during adolescence. Delineating neurodevelopmental trajectories associated with anxiety disorders is important for understanding the pathophysiology of pediatric anxiety and for early risk identification. While a growing literature has yielded valuable insights into the nature of brain structure and function in pediatric anxiety, progress has been limited by inconsistent findings and challenges common to neuroimaging research. In this review, we first discuss these challenges and the promise of ‘big data’ to map neurodevelopmental trajectories in pediatric anxiety. Next, we review evidence of age-related differences in neural structure and function among anxious youth, with a focus on anxiety-relevant processes such as threat and safety learning. We then highlight large-scale cross-sectional and longitudinal studies that assess anxiety and are well positioned to inform our understanding of neurodevelopment in pediatric anxiety. Finally, we detail relevant challenges of ‘big data’ and propose future directions through which large publicly available datasets can advance knowledge of deviations from normative brain development in anxiety. Leveraging ‘big data’ will be essential for continued progress in understanding the neurobiology of pediatric anxiety, with implications for identifying markers of risk and novel treatment targets.

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“…The current project is part of a larger series of studies within the HCP framework known collectively as the Human Connectome Studies Related to Human Disease (CRHD) and will contribute to building a database for comparisons between diverse populations. In particular, three other projects studying similar aspects of human psychopathology were funded at approximately the same time as the Anxious Misery project: Connectomes Related to Anxiety & Depression (PIs: Whitfield-Gabrieli & Gabrieli; Northeastern University & Massachusetts Institute of Technology) ( Hubbard, 2020 , Siless, 2020 ), Mapping Connectomes for Disordered Mental States (PI: Williams, Stanford University) ( Tozzi, 2020 ) and Perturbation of the Treatment of Resistant Depression Connectome by Fast-Acting Therapies (PIs: Espinoza, Narr, & Wang; University of California, Los Angeles) ( Loureiro et al, 2020 , Vasavada et al, 2020 ). Respectively focusing on adolescents, patients experiencing emotional dysregulation and treatment-resistant patients, each of these projects has slightly different goals and patient populations.…”

Section: Discussionmentioning

confidence: 99%

Dimensional connectomics of anxious misery, a human connectome study related to human disease: Overview of protocol and data quality

Seok

Smyk

Jaskir

et al. 2020

NeuroImage: Clinical

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Highlights We present a new imaging study of 200 adults experiencing depression and anxiety. Quantitative measures of image quality indicate comparable quality to the HCP-YA. In addition, a comprehensive set of assessments measured patients’ symptom profiles. Data will be publicly available through the NIMH Data Archive starting fall 2020.

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Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

Cited by 24 publications

References 148 publications

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders

Leveraging big data to map neurodevelopmental trajectories in pediatric anxiety

Dimensional connectomics of anxious misery, a human connectome study related to human disease: Overview of protocol and data quality

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