The Human Connectome Project of adolescent anxiety and depression dataset.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
02 Aug 2024
Historique:
received: 01 05 2024
accepted: 09 07 2024
medline: 3 8 2024
pubmed: 3 8 2024
entrez: 2 8 2024
Statut: epublish

Résumé

This article describes primary data and resources available from the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, a novel arm of the Human Connectome Project (HCP). Data were collected from 215 adolescents (14-17 years old), 152 of whom had current diagnoses of anxiety and/or depressive disorders at study intake. Data include cross-sectional structural (T1- and T2-weighted), functional (resting state and three tasks), and diffusion-weighted magnetic resonance images. Both unprocessed and HCP minimally-preprocessed imaging data are available within the data release packages. Adolescent and parent clinical interview data, as well as cognitive and neuropsychological data are also included within these packages. Release packages additionally provide data collected from self-report measures assessing key features of adolescent psychopathology, including: anxious and depressive symptom dimensions, behavioral inhibition/activation, exposure to stressful life events, and risk behaviors. Finally, the release packages include 6- and 12-month longitudinal data acquired from clinical measures. Data are publicly accessible through the National Institute of Mental Health Data Archive (ID: #2505).

Identifiants

pubmed: 39095370
doi: 10.1038/s41597-024-03629-x
pii: 10.1038/s41597-024-03629-x
doi:

Types de publication

Journal Article Dataset

Langues

eng

Sous-ensembles de citation

IM

Pagination

837

Subventions

Organisme : U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)
ID : P20GM130461-6206
Organisme : Brain and Behavior Research Foundation (Brain & Behavior Research Foundation)
ID : 27970
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : R01MH135488
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : R01MH119771
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : R01MH099021
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : R37MH068376
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : R01MH101521
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : U01MH108168
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : U01MH108168
Organisme : U.S. Department of Health & Human Services | NIH | National Center for Complementary and Integrative Health (NCCIH)
ID : R01AT007257
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB)
ID : R01EB021265
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB)
ID : U01EB026996
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB)
ID : R01EB020740
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB)
ID : P41EB019936

Informations de copyright

© 2024. The Author(s).

Références

Casey, B. J. Beyond simple models of self-control to circuit-based accounts of adolescent behavior. Annu. Rev. Psychol. 66, 295–319 (2015).
pubmed: 25089362 doi: 10.1146/annurev-psych-010814-015156
Somerville, L. H., Jones, R. M. & Casey, B. A time of change: Behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain Cogn 72, 124 (2010).
pubmed: 19695759 doi: 10.1016/j.bandc.2009.07.003
Auerbach, R. P., Webb, C. A., Gardiner, C. K. & Pechtel, P. Behavioral and neural mechanisms underlying cognitive vulnerability models of depression. Journal of Psychotherapy Integration 23, 222–235 (2013).
doi: 10.1037/a0031417
Hofmann, S. G., Ellard, K. K. & Siegle, G. J. Neurobiological correlates of cognitions in fear and anxiety: A cognitive–neurobiological information-processing model. Cognition & Emotion 26, 282–299 (2012).
doi: 10.1080/02699931.2011.579414
Pizzagalli, D. A. Depression, stress, and anhedonia: Toward a synthesis and integrated model. Annu Rev Clin Psychol 10, 393–423 (2014).
pubmed: 24471371 pmcid: 3972338 doi: 10.1146/annurev-clinpsy-050212-185606
Volkow, N. D. et al. The conception of the ABCD study: From substance use to a broad NIH collaboration. Developmental Cognitive Neuroscience 32, 4–7 (2018).
pubmed: 29051027 doi: 10.1016/j.dcn.2017.10.002
Schumann, G. et al. The imagen study: Reinforcement-related behaviour in normal brain function and psychopathology. Molecular Psychiatry 15, 1128–1139 (2010).
pubmed: 21102431 doi: 10.1038/mp.2010.4
Satterthwaite, T. D. et al. The Philadelphia neurodevelopmental cohort: A publicly available resource for the study of normal and abnormal brain development in youth. NeuroImage 124, 1115–1119 (2016).
pubmed: 25840117 doi: 10.1016/j.neuroimage.2015.03.056
Harms, M. P. et al. Extending the human connectome project across ages: Imaging protocols for the lifespan development and aging projects. NeuroImage 183, 972–984 (2018).
pubmed: 30261308 doi: 10.1016/j.neuroimage.2018.09.060
Somerville, L. H. et al. The lifespan human connectome project in development: A large-scale study of brain connectivity development in 5–21 year olds. NeuroImage 183, 456–468 (2018).
pubmed: 30142446 doi: 10.1016/j.neuroimage.2018.08.050
Elam, J. S. et al. The human connectome project: A retrospective. NeuroImage 244, 118543 (2021).
pubmed: 34508893 doi: 10.1016/j.neuroimage.2021.118543
Glasser, M. F. et al. The human connectome project’s neuroimaging approach. Nat Neurosci 19, 1175–1187 (2016).
pubmed: 27571196 pmcid: 6172654 doi: 10.1038/nn.4361
Siless, V. et al. Image acquisition and quality assurance in the Boston adolescent neuroimaging of depression and anxiety study. NeuroImage: Clinical 26, 102242 (2020).
pubmed: 32339824 doi: 10.1016/j.nicl.2020.102242
Kaufman, J. et al. Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry 36, 980–988 (1997).
doi: 10.1097/00004583-199707000-00021
American Psychiatric Association. Diagnostic and statistical manual of mental disorders, https://doi.org/10.1176/appi.books.9780890425596 (2013).
Weissman, M. M. et al. Brief screening for family psychiatric history: The family history screen. Archives of General Psychiatry 57, 675–682 (2000).
pubmed: 10891038 doi: 10.1001/archpsyc.57.7.675
Posner, K. et al. The Columbia–suicide severity rating scale: Initial validity and internal consistency findings from three multisite studies with adolescents and adults. Am J Psychiatry 168, 1266–1277 (2011).
pubmed: 22193671 pmcid: 3893686 doi: 10.1176/appi.ajp.2011.10111704
Wechsler, D. Wechsler Abbreviated Scale of Intelligence, Second Edition, https://doi.org/10.1037/t15171-000 (2011).
Harris, P. A. et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 42, 377–381 (2009).
pubmed: 18929686 doi: 10.1016/j.jbi.2008.08.010
Freedman, R. et al. The initial field trials of DSM-5: New blooms and old thorns. American Journal of Psychiatry 170, 1–5 (2013).
pubmed: 23288382 doi: 10.1176/appi.ajp.2012.12091189
Hubbard, N. A. et al. Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study. NeuroImage: Clinical 27, 102240 (2020).
pubmed: 32361633 doi: 10.1016/j.nicl.2020.102240
Taylor, S. J. et al. Performance of a new pubertal self‐assessment questionnaire: A preliminary study. Paediatric and Perinatal Epidemiology 15, 88–94 (2001).
pubmed: 11237120 doi: 10.1046/j.1365-3016.2001.00317.x
Chapman, L. J. & Chapman, J. P. The measurement of handedness. Brain and Cognition 6, 175–183 (1987).
pubmed: 3593557 doi: 10.1016/0278-2626(87)90118-7
Slavich, G. M., Stewart, J. G., Esposito, E. C., Shields, G. S. & Auerbach, R. P. The stress and adversity inventory for adolescents (adolescent STRAIN): Associations with mental and physical health, risky behaviors, and psychiatric diagnoses in youth seeking treatment. Child Psychology Psychiatry 60, 998–1009 (2019).
doi: 10.1111/jcpp.13038
Gershon, R. C. et al. NIH toolbox for assessment of neurological and behavioral function. Neurology 80 (2013).
Heaton, R. K. et al. Reliability and validity of composite scores from the NIH toolbox cognition battery in adults. J Int Neuropsychol Soc 20, 588–598 (2014).
pubmed: 24960398 pmcid: 4103963 doi: 10.1017/S1355617714000241
Gur, R. C. et al. A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: Standardization and initial construct validation. Journal of Neuroscience Methods 187, 254–262 (2010).
pubmed: 19945485 doi: 10.1016/j.jneumeth.2009.11.017
Marcus, D. S. et al. Human connectome project informatics: Quality control, database services, and data visualization. NeuroImage 80, 202–219 (2013).
pubmed: 23707591 doi: 10.1016/j.neuroimage.2013.05.077
Tisdall, M. D. et al. Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI. Magnetic Resonance in Med 68, 389–399 (2012).
doi: 10.1002/mrm.23228
Delgado, M. R., Nystrom, L. E., Fissell, C., Noll, D. C. & Fiez, J. A. Tracking the hemodynamic responses to reward and punishment in the striatum. Journal of Neurophysiology 84, 3072–3077 (2000).
pubmed: 11110834 doi: 10.1152/jn.2000.84.6.3072
Barch, D. M. et al. Function in the human connectome: Task-FMRI and individual differences in behavior. NeuroImage 80, 169–189 (2013).
pubmed: 23684877 doi: 10.1016/j.neuroimage.2013.05.033
Chai, X. J. et al. Functional and structural brain correlates of risk for major depression in children with familial depression. NeuroImage: Clinical 8, 398–407 (2015).
pubmed: 26106565 doi: 10.1016/j.nicl.2015.05.004
Hariri, A. R., Tessitore, A., Mattay, V. S., Fera, F. & Weinberger, D. R. The amygdala response to emotional stimuli: A comparison of faces and scenes. NeuroImage 17, 317–323 (2002).
pubmed: 12482086 doi: 10.1006/nimg.2002.1179
Fales, C. L. et al. Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biological Psychiatry 63, 377–384 (2008).
pubmed: 17719567 doi: 10.1016/j.biopsych.2007.06.012
Vuilleumier, P., Armony, J. L., Driver, J. & Dolan, R. J. Effects of attention and emotion on face processing in the human brain. Neuron 30, 829–841 (2001).
pubmed: 11430815 doi: 10.1016/S0896-6273(01)00328-2
Wojciulik, E., Kanwisher, N. & Driver, J. Covert visual attention modulates face-specific activity in the human fusiform gyrus: Fmri study. Journal of Neurophysiology 79, 1574–1578 (1998).
pubmed: 9497433 doi: 10.1152/jn.1998.79.3.1574
Marcus, D. S., Olsen, T. R., Ramaratnam, M. & Buckner, R. L. The extensible neuroimaging archive toolkit: An informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics 5, 11–33 (2007).
pubmed: 17426351 doi: 10.1385/NI:5:1:11
Glasser, M. F. et al. The minimal preprocessing pipelines for the human connectome project. Neuroimage 80, 105–124 (2013).
pubmed: 23668970 doi: 10.1016/j.neuroimage.2013.04.127
Bastiani, M. et al. Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction. NeuroImage 184, 801–812 (2019).
pubmed: 30267859 doi: 10.1016/j.neuroimage.2018.09.073
Elam, J. et al. Data repository for: Boston adolescent neuroimaging of depression & anxiety (BANDA) release 1.1. NIMH Data Repositories https://doi.org/10.15154/3TK5-PB47 (2024).
Ji, J. L. et al. QuNex—an integrative platform for reproducible neuroimaging analytics. Frontiers in Neuroinformatics 17, (2023).
McInnes, L., Healy, J. & Melville, J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. Preprint at http://arxiv.org/abs/1802.03426 (2020).
Meehan, C., Ebrahimian, J., Moor, W. & Meehan, S. Uniform manifold approximation and projection (UMAP). MathWorks File Exchange Available at: https://www.mathworks.com/matlabcentral/fileexchange/71902-uniform-manifold-approximation-and-projection-umap . (Last Accessed: 6th April 2024) (2022).
Cox, R. W. AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research 29, 162–173 (1996).
pubmed: 8812068 doi: 10.1006/cbmr.1996.0014
Hubbard, N. A. et al. Connectivity patterns evoked by fearful faces demonstrate reduced flexibility across a shared dimension of adolescent anxiety and depression. Clinical Psychological Science 11, 3–22 (2023).
doi: 10.1177/21677026221079628
Haxby, J. V., Hoffman, E. A. & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Sciences 4, 223–233 (2000).
pubmed: 10827445 doi: 10.1016/S1364-6613(00)01482-0
Hubbard, N. A. et al. Reward-sensitive basal ganglia stabilize the maintenance of goal-relevant neural patterns in adolescents. Journal of Cognitive Neuroscience 32, 1508–1524 (2020).
pubmed: 32379000 pmcid: 8500599 doi: 10.1162/jocn_a_01572
Hubbard, N. A. et al. Resting cerebral oxygen metabolism exhibits archetypal network features. Human Brain Mapping 42, 1952–1968 (2021).
pubmed: 33544446 pmcid: 8046048 doi: 10.1002/hbm.25352
Whitfield-Gabrieli, S. & Ford, J. M. Default mode network activity and connectivity in psychopathology. Annu. Rev. Clin. Psychol. 8, 49–76 (2012).
pubmed: 22224834 doi: 10.1146/annurev-clinpsy-032511-143049
Raichle, M. E. Two views of brain function. Trends in Cognitive Sciences 14, 180–190 (2010).
pubmed: 20206576 doi: 10.1016/j.tics.2010.01.008
Hubbard, N. A., Bauer, C. C. C., Siless, V., Elam, J., & Ghosh, S. S. Resource repository for: BANDA resources and materials data release v1.1 (BANDA_v1.1_data_release). Zenodo https://doi.org/10.5281/zenodo.10849500 (2024).
Siless, V. & Bauer, C. C. C. Source code repository for: BANDA fMRI task code. Zenodo https://doi.org/10.5281/zenodo.10851055 (2024).
Auerbach, R. P. et al. Reward-related neural circuitry in depressed and anxious adolescents: A Human Connectome Project. J Amer Academy of Child and Adol Psychi 61, 308–320 (2022).
doi: 10.1016/j.jaac.2021.04.014

Auteurs

N A Hubbard (NA)

Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA. nhubbard5@unl.edu.
Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA. nhubbard5@unl.edu.

C C C Bauer (CCC)

Department of Psychology, Northeastern University, Boston, MA, USA.
Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

V Siless (V)

Harvard Medical School, Boston, MA, USA.
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.

R P Auerbach (RP)

Department of Psychiatry, Columbia University, New York, NY, USA.

J S Elam (JS)

Department of Neuroscience, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.

I R Frosch (IR)

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

A Henin (A)

Harvard Medical School, Boston, MA, USA.
Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.

S G Hofmann (SG)

Department of Psychology, Philipps University of Marburg, DEU, Germany.

M R Hodge (MR)

Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.

R Jones (R)

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.

P Lenzini (P)

Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.

N Lo (N)

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

A T Park (AT)

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

D A Pizzagalli (DA)

Harvard Medical School, Boston, MA, USA.
Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.

F Vaz-DeSouza (F)

Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.

J D E Gabrieli (JDE)

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

S Whitfield-Gabrieli (S)

Department of Psychology, Northeastern University, Boston, MA, USA.
Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

A Yendiki (A)

Harvard Medical School, Boston, MA, USA.
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.

S S Ghosh (SS)

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA. satra@mit.edu.
Harvard Medical School, Boston, MA, USA. satra@mit.edu.

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