Advertisement

BioSocieties

, Volume 11, Issue 3, pp 296–316 | Cite as

Big data, small kids: Medico-scientific, familial and advocacy visions of human brains

  • Rayna RappEmail author
Original Article

Abstract

On the basis of anthropological fieldwork in a US pediatric neuroscience laboratory, this article traces the recent move from studies of individual diagnostic pathologies like ADHD, Tourette or autism spectrum disorder to the rapid creation of innovative interdisciplinary research coalitions and collaborations that both produce and utilize big data techniques in order to map the human connectome. By analogy with the human genome, connectome studies require new ways to imagine and image complex and multivalent neuro-circuits in which brain scans of those with and without diagnoses provide data points, open to recombination with other forms of data. Emergent expert understandings of the connectome are only minimally related to what families who enroll their diagnosed children in fMRI studies understand. Likewise, young adult self-advocates with the same diagnoses on which the neuroscientists are now working use ‘brain talk’ to stake their own ethical claims. I argue that this epistemological gap among medico-scientific, familial and advocacy visions of human brains provides a mobile space of creativity as well as misunderstanding.

Keywords

big data neuroscience childhood disability medical anthropology connectome 

Notes

Acknowledgements

Portions of this study were funded by a collaborative research grant on “cultural innovation in learning disabilities” from the Spencer Foundation; by a seed grant from NYU’s Institute for the Study of Human Development and Social Change (both with Faye Ginsburg); and by a John Simon Guggenheim Fellowship. Thanks are due to members of the lab described in this essay for their hospitality and willingness to answer the author’s continual questions, and to the many families and self-advocates interviewed. Several lab members responded with thoughtful and enthusiastic questions and suggestions when the author presented the penultimate version of this article at their journal club. Additionally, the author is as always deeply grateful to Faye Ginsburg for their longstanding and shared research and writing partnership. Questions and suggestions made by three anonymous reviewers for BioSocieties greatly improved this article.

The material included in this essay is wholly original with the exception of 509 words that are ethnographic quotations of parents’ responses to brain scanning of their children. These are lightly revised from a prior chapter, “A Child Surrounds This Brain: the Future of Neurological Difference According to Scientists, Parents, and Diagnosed Young Adults” in Martyn Pickersgill & Ira Vankeulen eds., 2011. Sociological Reflections on the Neurosciences. London: Emerald: 3–26.

This study was approved by the Institutional Review Board of New York University, beginning in 2007 with various renewals.

I have no competing intellectual or financial interests.

References

  1. Advisors Report (2014) NIH accepts scientific vision for the BRAIN initiative, http://brainfeedback.nih.gov/nih-accepts-scientific-vision-for-brain-initiative/, accessed 9 June 2014.
  2. Alberts, B. (2012) Editorial. Science, 336. 13 April, p. 131.Google Scholar
  3. Autistic Self Advocacy Network (ASAN). Autistic self-advocacy, http://www.autisticadvocacy.org/, accessed 11 July 2014.
  4. Bardin, J. (2012) Neuroscience: Making connections. Nature 483: 394–396.CrossRefGoogle Scholar
  5. Bascom, J. (2012) Loud Hands: Autistic People, Speaking. Washington DC: Autism Self-Advocacy Network Press.Google Scholar
  6. Bettelheim, B. (1967) The Empty Fortress: Infantile Autism and the Birth of the Self. Washington DC: National Academies Press.Google Scholar
  7. Biswal, B. (2012) Resting state fMRI: A personal history. Neuroimage 62(2): 938–944.CrossRefGoogle Scholar
  8. Biswal, B. et al (2010) Toward discovery science of human brain function. PNAS 107(10): 4734–4739.CrossRefGoogle Scholar
  9. Boyd, D. and Crawford, K. (2012) Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication, & Society 15(5): 662–679.CrossRefGoogle Scholar
  10. Callard, F. (2014) Psychiatric diagnosis: The indispensability of ambivalence. J Medical Ethics 40(8): 526–530.CrossRefGoogle Scholar
  11. Callard, F. and Margulies, D. (2011) The subject at rest: Novel conceptualizations of self and brain from cognitive neuroscience’s study of the ‘resting state’. Subjectivity 4(3): 227–257.CrossRefGoogle Scholar
  12. Canguilhem, G. (1993) The normal and the pathological. In: F. Delaport (ed.) A Vital Rationalist: Selected Writings from Georges Canguilhem. New York: Zone Books, pp. 321–325.Google Scholar
  13. Cacioppo, S., Weiss, R., Runesha, H.B. and Cacioppo, J.T. (2014) Dynamic spatiotemporal brain analyses using high performance electrical neuroimaging: Theoretical framework and validation. Journal of Neuroscience Methods 238, 30 December.Google Scholar
  14. Carlson, L. (2010) The Faces of Intellectual Disability: Philosophical Reflections. Bloomington, IN: Indiana University Press.Google Scholar
  15. Cohn, S. (2012) Disrupting images: Neuroscientific representations in the lives of psychiatric patients. In: S. Choudhury and J. Staby (eds.) Critical Neuroscience, A Handbook of the Social and Cultural Contexts of Neuroscience. Malden, MA: Wiley, pp. 179–193.Google Scholar
  16. Collins, F.S. (1995) Ahead of schedule and under budget: The genome project passes its fifth birthday. Proceedings of the National Academy of Sciences of the United States of America 92(24): 10821–1082.Google Scholar
  17. Danforth, S. (2009) The Incomplete Child: An Intellectual History of Learning Disabilities. New York: Peter Lang.Google Scholar
  18. Davidson, J. and Orsini, M. (eds.) (2013) Worlds of Autism: Across the Spectrum of Neurological Difference. Minneapolis, MN: University of Minnesota Press.CrossRefGoogle Scholar
  19. Davies, G., Frow, E. and Leonelli, S. (2013) Bigger, faster, better? Rhetorics and practices of large-scale research in contemporary bioscience. BioSocieties 8: 386–396.CrossRefGoogle Scholar
  20. Davis, L. (ed.) (2013) The Disability Studies Reader. New York: Routledge.Google Scholar
  21. De Rijcke, S. and Beaulieu, A. (2014) Networked neuroscience: Brain scans and visual knowing at the intersection of atlases and databases. In: C. Coopmans, J. Vertesi, M. Lynch and S. Woolgar (eds.) (2014) Representation in Scientific Practice Revisited. Cambridge, US: MIT Press, pp. 131–152.CrossRefGoogle Scholar
  22. Di Martino, A. et al (2008) Functional connectivity of human striatum: A resting state fMRI study. Cerebral Cortex 18(12): 2735–2747.CrossRefGoogle Scholar
  23. Director’s Blog (2014) The symphony inside your brain, http://directorsblog.nih.gov/2012/11/05/the-symphony-inside-your-brain/, accessed 15 June 2014.
  24. Dumit, J. (2004) Picturing Personhood: Brain Scans and Biomedical Identity. Princeton, NJ: Princeton University Press.Google Scholar
  25. Dumit, J. (2012) Drugs for Life: How Pharmaceutical Companies Define our Health. Durham, NC: Duke University Press.CrossRefGoogle Scholar
  26. Dumit, J. (2014) How (not) to do things with brain images. In: C. Coopmans, J. Vertesi, M. Lynch and S. Wadgar (eds.) Representation in Scientific Practice Revisited. Cambridge, US: MIT Press, pp. 291–313.CrossRefGoogle Scholar
  27. Eye-to-Eye National. http://www.eyetoeyenational.org/, accessed 11 July 2014.
  28. Geertz, C. (1974) From the native’s point of view: On the nature of anthropological understanding. Bulletin of American Academy of Arts and Sciences 28(1): 26–43.CrossRefGoogle Scholar
  29. Ginsburg, F. (2012) Disability in the digital age. In: H. Horst and D. Miller (eds.) Digital Anthropology. London: Bloomsbury Publishers, pp. 101–126.Google Scholar
  30. Ginsburg, F. and Rapp, R. (2015a) “Not dead yet”: Changing disability imaginaries in 21st century America. In: V. Das and C. Han (eds.) An Anthropology of Living and Dying. Berkeley; Los Angeles, CA: University of California Press, pp. 525–541.Google Scholar
  31. Ginsburg, F. and Rapp, R. (2015b) Families. In: R. Adams, B. Reiss and D. Serlin (eds.) Keywords in Disability Studies. New York: NYU Press, pp. 81–84.Google Scholar
  32. Ginsburg, F. and Rapp, R. (2015c) Screening disabilities: Atypical minds in the early 21st century. In: N. Hirschmann and B.l. Linker (eds.) Civil Disabilities: Citizenship, Membership and Belonging. Philadelphia, PA: University Pennsylvania Press, pp. 103–122.Google Scholar
  33. Ginsburg, F. and Rapp, R. (2013a) Entangled ethnography: Imagining a future for young adults with learning disabilities. Social Science & Medicine 99(11): 187–193.CrossRefGoogle Scholar
  34. Ginsburg, F. and Rapp, R. (2013b) Disability worlds. Annual Review Anthropology 42: 53–68.CrossRefGoogle Scholar
  35. Ginsburg, F. and Rapp, R. (2012) Anthropology and the study of disability worlds. In: M. Inhorn and E. Wertzel (eds.) Medical Anthropology at the Intersections. Durham, NC: Duke University Press, pp. 163–182.Google Scholar
  36. Gopalan, P. and Blei, D. (2013) Efficient discovery of overlapping communities in massive networks. Proceedings of the National Academy of Sciences 110(36): 14534–14539.CrossRefGoogle Scholar
  37. Hart, B. (2014) Autism parents & neurodiversity: Radical translation, joint embodiment and the prosthetic environment. BioSocieties 9(3): 284–303.CrossRefGoogle Scholar
  38. Hagmann, P. (2005) From diffusion MRI to brain connectomics, EPFL, University of Laussane, Lausanne, Switzerland accessed 10 July 2014.Google Scholar
  39. Hilgartner, S. (2013) Constituting large-scale biology: Building a regime of governance in the early years of the Human Genome Project. BioSocieties 8: 397–416.CrossRefGoogle Scholar
  40. Hirschmann, N. and Linker, B. (2015) Civil Disabilities: Citizenship, Membership and Belonging. Philadelphia, PA: University of Pennsylvania Press.CrossRefGoogle Scholar
  41. Hoeyer, K. (2007) Person, patent, and property: A critique of the commodification hypothesis. BioSocieties 2: 327–348.CrossRefGoogle Scholar
  42. Hoeyer, K. and Hogle, L. (2014) Informed consent: The politics of intent and practice in medical research ethics. Annual Review of Anthropology 43: 347–362.CrossRefGoogle Scholar
  43. Hogle, L. (2013) Big data and big biomedicine. Paper presented at the Society for the Social Study of Science Annual Meeting; 10 August, San Diego, CA.Google Scholar
  44. Human Connectome Project. http://www.humanconnectomeproject.org, accessed 10 August 2014.
  45. Icarus Project. http://www.theicarusproject.org, accessed 10 August 2014.
  46. Ingalhalikar, M., Parker, W.A., Bloy, L., Roberts, T.P.L. and Verma, R. (2014) Creating multimodal predictors using missing data: Classifying and subtyping autism spectrum disorder. Journal of Neuroscience Methods 28 June 235(30): 1–9.Google Scholar
  47. Insel, T. (2013) Transforming diagnosis, http://www.nimh.nih.gov/about/director/2013/transforming-diagnosis.shtml, accessed 25 January 2015.
  48. Kanner, L.J. (1943) Autistic disturbances of affective contact. Nervous Child 2: 217–250.Google Scholar
  49. Keller, E.F. (2010) The Mirage of a Space Between Nature and Nurture. Durham, NC: Duke University Press.CrossRefGoogle Scholar
  50. Keller, E.F. (2013) Three questions, http://newsoffice.mit.edu/2010/3q-keller-1129, accessed 9 June 2014.
  51. Keller, E.F. (Forthcoming) Epigenetics and society: Expectations, potentials, criticisms. In: M. Meloni, S. Williams and P. Martin (eds.) Biosocial Matters: Rethinking Sociology-Biology Relations in the Twenty-First Century. West Sussex, UK: Wiley-Blackwell, in press.Google Scholar
  52. Lappe, M. (2014) Taking care: Anticipation, extraction and the politics of temporality in autism science. BioSocieties 9: 304–328.CrossRefGoogle Scholar
  53. Levina, M. (2010) Googling your genes: Personal genomics and the discourse of citizen bioscience in the network age. Journal of Science Communication 9(1): 1–8.Google Scholar
  54. Lichtman, J. and Sanes, J. (2008) Ome sweet ome: What can the genome tell us about the connectome? Current Opinion in Neurobiology 18(3): 346–353.CrossRefGoogle Scholar
  55. Martin, E. (2010) BiPolar Expeditions: Mania and Depression in American Culture. Princeton, NJ: Princeton University Press.Google Scholar
  56. Miller, P. and Rose, N. (1990) Governing economic life. Economy & Society 19(1): 1–31.CrossRefGoogle Scholar
  57. National Center for Advancing Translational Sciences. http://www.ncats.nih.gov/about/org/organization.html, accessed 11 June 2014.
  58. NIH Blueprint for Neuroscience Research. http://neuroscienceblueprint.nih.gov/, accessed 9 June 2014.
  59. Ortega, F. (2009) The cerebral subject and the challenge of neurodiversity. Biosocieties 4(3): 425–445.CrossRefGoogle Scholar
  60. Ossorio, P. (2012) Taking aims seriously: Repository research and limits on the duty to return individual research findings. Genetics in Medicine 14(4): 461.CrossRefGoogle Scholar
  61. Ossorio, P. (2011) Bodies of data: Genomic data and bioscience data sharing. Journal of Social Research 78(3): 907–932.Google Scholar
  62. Pickersgill, M. (2014) Debating DSM-5: Diagnosis and the sociology of critique. J Medical Ethics 40(8): 521–525.CrossRefGoogle Scholar
  63. Pickersgill, M. and Cunningham-Burley, S. (2011) Constituting neurologic subjects: Neuroscience, subjectivity, and the mundane significance of the brain. Subjectivity 4: 346–365.CrossRefGoogle Scholar
  64. Plitt, M., Barnes, K.A. and Martin, A. (2015) Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards. Neuroimage 7(7): 359–366.CrossRefGoogle Scholar
  65. Rapp, R. (2012) A child surrounds this brain: The future of neurological difference according to scientists, parents, and diagnosed young adults. In: M. Pickersgill and I. Vankeulen (eds.) Sociological Reflections on the Neurosciences. London: Emerald, pp. 3–26.Google Scholar
  66. Rapp, R. (2011) Chasing science: Children’s brains, scientific technologies, family participation. Science, Technology & Human Values 36(5): 662–684.CrossRefGoogle Scholar
  67. Rapp, R. and Ginsburg, F. (2011a) Reverberations: Disability and the kinship imaginary. Anthropological Quarterly 84(2): 379–410.CrossRefGoogle Scholar
  68. Rapp, R. and Ginsburg, F. (2011b) The paradox of recognition: Success or stigma for children with learning disabilities. In: J. McLaughlin, P. Phillimore and D. Richardson (eds.) Contesting Recognition: Culture, Identity and Citizenship. London: Palgrave Macmillan, pp. 166–186.CrossRefGoogle Scholar
  69. Rose, N. (1999) The Powers of Freedom: Reframing Political Thought. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  70. Rose, N. (2009) The Politics of Life Itself: Biomedicine, Power and Subjectivity in the Twenty-First Century. Princeton, NJ: Princeton University Press.Google Scholar
  71. Rose, N. and Abi-Rached, J.M. (2013) Neuro: The New Brain Sciences and the Management of the Mind. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
  72. Shapiro, F.B. and Ossorio, P. (2013) Regulation of online social network research. Science 339(6116): 144.CrossRefGoogle Scholar
  73. Shapiro, J. (1994) No Pity: People with Disabilities Forging a New Civil Rights Movement. New York: Broadway Books.Google Scholar
  74. Shehzad, Z. et al (2009) The resting brain: Unconstrained yet reliable. Cerebral Cortex 19(10): 2209–2229.CrossRefGoogle Scholar
  75. Silverman, C. (2011) Understanding Autism: Parents, Doctors, and the History of a Disorder. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
  76. Singh, I. (2004) Doing their jobs: Mothering with Ritalin in a culture of mother-blame. Social Science and Medicine 59(6): 1193–1205.CrossRefGoogle Scholar
  77. Singh, I. (2011) A disorder of anger and aggression: Children’s perspectives on attention deficit/hyperactivity disorder in the UK. Social Science and Medicine 73(6): 889–896.CrossRefGoogle Scholar
  78. Singh, I. (2013) Brain-talk: Power and negotiation in children’s discourse about self, brain and behaviour. Sociology of Health and Illness 35(6): 813–827.CrossRefGoogle Scholar
  79. Szmukler, G. (2014) When psychiatric diagnosis becomes an overworked tool. J Medical Ethics 40(8): 517–520.CrossRefGoogle Scholar
  80. Sporns, O., Tononi, G. and Kötter, R. (2005) The human connectome: A structural description of the human brain. PLoS Computational Biology 1(4): e42.CrossRefGoogle Scholar
  81. Stevens, H. (2013) Life Out of Sequence: A Data-driven History of Bioinformatics. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
  82. Stiker, H.-J. and Sayers, W. (2000) A History of Disability. Ann Arbor, MI: University of Michigan Press.CrossRefGoogle Scholar
  83. Sullivan, J. (2013) Forget the needle, consider the haystack: Uncovering hidden structures in massive data collections. Communication of the ACM www.princeton.edu/main/news/archive838/25/36G63 index/xml, accessed 6 August 2015.
  84. Trent, J. (1994) Inventing the Feeble Mind: A History of Mental Retardation in the United States. Berkeley, CA: University of California Press.Google Scholar
  85. Van Essen, D. et al (2012) The human connectome project: A data acquisition perspective. NeuroImage 62(4): 2222–2231, http://www.poetryfoundation.org/poem/174745, accessed 26 August.CrossRefGoogle Scholar
  86. Vidal, F. (2011) Fiction, film, and the cerebral subject. In: F. Ortega and F. Vidal (eds.) Neurocultures: Glimpses into an Expanding Universe. Frankfurt, Germany: Lang, pp. 329–344.Google Scholar
  87. Whitman, W. (1855) Song of Myself, http://www.poetryfoundation.org/poem/174745, accessed 26 August.
  88. Wooley, O. (2014) Nosological reflections: The failure of DSM-5, the emergence of RDoC, and the decontextualization of mental distress. Society and Mental Health 4(2): 92–110.CrossRefGoogle Scholar

Copyright information

© Macmillan Publishers Ltd 2016

Authors and Affiliations

  1. 1.Anthropology Department, New York UniversityNew YorkUSA

Personalised recommendations