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An open resource for transdiagnostic research in pediatric mental health and learning disorders

Lindsay M. Alexander, Jasmine Escalera, Lei Ai and 64 more

Scientific Data · 2017 · CC BY-NC-SA

doi:10.1101/149369

Abstract

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5–21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release ( n =664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

References 92

  1. 1.

    Functional Connectomes Project International Neuroimaging Data-Sharing Initiative2017 http://dx.doi.org/10.15387/CMI_HBN

    Not in our library

  2. 2.

    Kessler R. C. et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 593–602 (2005 ).

    Not in our library10.1001/archpsyc.62.6.593

  3. 3.

    Di Martino A. et al. Unraveling the miswired connectome: a developmental perspective. Neuron 83, 1335–1353 (2014 ).

    Not in our library10.1016/j.neuron.2014.08.050

  4. 4.

    Insel T. R. & Cuthbert B. N. Medicine. Brain disorders? Precisely. Science 348, 499–500 (2015 ).

    Not in our library10.1126/science.aab2358

  5. 5.

    Kapur S., Phillips A. G. & Insel T. R. Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Mol. Psychiatry 17, 1174–1179 (2012 ).

    Not in our library10.1038/mp.2012.105

  6. 6.

    Milham M. P., Craddock R. C. & Klein A. Clinically useful brain imaging for neuropsychiatry: How can we get there? Depress. Anxiety 34, 578–587 (2017 ).

    Not in our library10.1002/da.22627

  7. 7.
  8. 8.

    Insel T. et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167, 748–751 (2010 ).

    Not in our library10.1176/appi.ajp.2010.09091379

  9. 9.

    Fair D. A., Bathula D., Nikolas M. A. & Nigg J. T. Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD. Proc. Natl. Acad. Sci. USA. 109, 6769–6774 (2012 ).

    Not in our library10.1073/pnas.1115365109

  10. 10.
  11. 11.

    Van Dam N. T. et al. Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels. Biol. Psychiatry 81, 484–494 (2016 ).

    Not in our library10.1016/j.biopsych.2016.06.027

  12. 12.

    Paus T. Population neuroscience: Why and how. Hum. Brain Mapp. 31, 891–903 (2010 ).

    Not in our library10.1002/hbm.21069

  13. 13.
  14. 14.

    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. J. Am. Acad. Child Adolesc. Psychiatry 36, 980–988 (1997 ).

    Not in our library10.1097/00004583-199707000-00021

  15. 15.

    Lord C. et al. Autism diagnostic observation schedule--2nd edition (ADOS-2) (Western Psychological Corporation, 2012 ).

    Not in our library

  16. 16.

    Semel E. M., Wiig E. H. & Secord W. CELF3: clinical evaluation of language fundamentals (Psychological Corporation, 1995 ).

    Not in our library

  17. 17.

    Wechsler D. Wechsler intelligence scale for children--Fourth Edition (WISC-IV) (The Psychological Corporation, 2003 ).

    Not in our library

  18. 18.

    Kaufman A. S. & Kaufman N. L. in Encyclopedia of Special Education (John Wiley & Sons, Inc., 2013 ).

    Not in our library

  19. 19.

    Wechsler D. Wechsler Adult Intelligence Scale--Fourth edition (WAIS-IV), Australian and New Zealand Language Adaptation (NCS Pearson Inc, 2008 ).

    Not in our library

  20. 20.

    Test W. D. W. I. A. (WIAT II) (The Psychological Corp, 2005 ).

    Not in our library

  21. 21.

    Goldman R. GFTA-3: Goldman-Fristoe test of articulation 3. (Pearson, 2015).

    Not in our library

  22. 22.

    Wagner R. K., Torgesen J. K., Rashotte C. A. & Pearson N. A. Comprehensive Test of Phonological Processing: CTOPP2. (Pearson, 2013).

    Not in our library

  23. 23.

    Torgesen J. K., Wagner R. K. & Rashotte C. A. TOWRE: Test of word reading efficiency (Psychological Corporation, 1999 ).

    Not in our library

  24. 24.

    Wiig E. H., Semel E. M. & Secord W. CELF 5: Clinical Evaluation of Language Fundamentals (Pearson/PsychCorp, 2003 ).

    Not in our library

  25. 25.

    Williams K. T. EVT-2: Expressive vocabulary test (Pearson Assessments, 2007 ).

    Not in our library

  26. 26.

    Dunn L. M. & Dunn D. M. PPVT-4: Peabody picture vocabulary test (Pearson Assessments, 2007 ).

    Not in our library

  27. 27.

    Achenbach T. M. Integrative manual for the 1991 CBCL/4-18, YSR, and TRF profiles (University of Vermont, Department of Psychiatry, 1991 ).

    Not in our library

  28. 28.

    Gershon R. C. et al. NIH toolbox for assessment of neurological and behavioral function. Neurology 80, S2–S6 (2013 ).

    Not in our library10.1212/wnl.0b013e3182872e5f

  29. 29.

    Koffarnus M. N. & Bickel W. K. A 5-trial adjusting delay discounting task: accurate discount rates in less than one minute. Exp. Clin. Psychopharmacol. 22, 222–228 (2014 ).

    Not in our library10.1037/a0035973

  30. 30.

    The Cooper Institute. Fitnessgram and Activitygram Test Administration Manual-Updated. 4th edn (Human Kinetics, 2010 ).

    Not in our library

  31. 31.

    Langer N. et al. A resource for assessing information processing in the developing brain using EEG and eye tracking. Sci Data 4, 170040 (2017 ).

    Not in our library10.1038/sdata.2017.40

  32. 32.

    Moeller S. et al. Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI. Magn. Reson. Med. 63, 1144–1153 (2010 ).

    Not in our library10.1002/mrm.22361

  33. 33.
  34. 34.

    Sathian K. et al. Dual pathways for haptic and visual perception of spatial and texture information. Neuroimage 57, 462–475 (2011 ).

    Not in our library10.1016/j.neuroimage.2011.05.001

  35. 35.

    LaConte, S., Glielmi, C., Heberlein, K. & Hu, X. Verifying visual fixation to improve fMRI with predictive eye estimation regression (PEER). Proc. Intl. Soc. Magn. Reson. Med. 15, 3438 (2007).

    Not in our library

  36. 36.

    LaConte, S., Peltier, S., Heberlein, K. & Hu, X. Predictive eye estimation regression (PEER) for simultaneous eye tracking and fMRI. Proc. Intl. Soc. Magn. Reson. Med. 14, 2808 (2006).

    Not in our library

  37. 37.

    Sano, A. et al. Recognizing Academic Performance, Sleep Quality, Stress Level, and Mental Health using Personality Traits, Wearable Sensors and Mobile Phones. Int Conf Wearable Implant Body Sens Netw 2015, 1-6 (2015).

    Not in our library10.1109/bsn.2015.7299420

  38. 38.

    Cohen A. S., Renshaw T. L., Mitchell K. R. & Kim Y. A psychometric investigation of ‘macroscopic’ speech measures for clinical and psychological science. Behav Res 48, 475–486 (2016 ).

    Not in our library10.3758/s13428-015-0584-1

  39. 39.

    Ghosh S. S., Ciccarelli G., Quatieri T. F. & Klein A. Speaking one’s mind: Vocal biomarkers of depression and Parkinson disease. J. Acoust. Soc. Am. 139, 2193–2193 (2016 ).

    Not in our library

  40. 40.

    Markova D. et al. Age- and sex-related variations in vocal-tract morphology and voice acoustics during adolescence. Horm. Behav. 81, 84–96 (2016 ).

    Not in our library10.1016/j.yhbeh.2016.03.001

All 92 references

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