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What is a representative brain? Neuroscience meets population science

  1. John Schulenbergd,e,f,4
  1. Departments of aCommunication Studies,
  2. dPsychology,
  3. hStatistics,
  4. iPsychiatry,
  5. jPediatrics and Communicable Diseases,
  6. kInternal Medicine,
  7. nBiomedical Engineering;
  8. oNeuroscience Graduate Program;
  9. bResearch Center for Group Dynamics,
  10. eSurvey Research Center, and
  11. gPopulation Studies Center of the Institute for Social Research; and
  12. fCenter for Human Growth and Development, University of Michigan, Ann Arbor, MI 48109;
  13. cAnnenberg School for Communication, University of Pennsylvania, Philadephia, PA, 19104;
  14. lVeterans Affairs Center for Clinical Management Research, Ann Arbor, MI 48105,
  15. mRobert Wood Johnson Foundation Health and Society Scholars Program, Population Health Sciences, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI 53706;
  16. pSchool of Medicine Pediatrics and
  17. qMerrill Palmer Skillman Institute for Child and Family Development, Wayne State University, Detroit, MI 48202; and
  18. rPerinatology Research Branch, National Institutes of Health, Detroit, MI 48202
  1. Edited by Mary C. Waters, Harvard University, Cambridge, MA, and approved September 11, 2013 (received for review May 31, 2013)

Abstract

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.

Footnotes

  • 1E.B.F., L.W.H., and C.M. contributed equally to this work.

  • 2To whom correspondence should be addressed. E-mail: cmsm{at}umich.edu.
  • 3J.F., R.G., M.M.H., D.P.K., K.M.L., M.E.M., J.M., F.J.M., D.C.N., M.E.P., F.T.P., P.A.R.-L., and M.E.T. contributed equally to this work.

  • 4P.D.-K., C.S.M., and J.S. contributed equally to this work.

  • Author contributions: P.D.-K., C.S.M. and J.S. formed and led group; E.B.F., L.W.H., and C.M. wrote paper; and E.B.F., L.W.H., C.M., J.F., R.G., M.M.H., D.P.K., K.M.L., M.E.M., J.M., F.J.M., D.C.N., M.E.P., F.T.P., P.A.R.-L., M.E.T., P.D.-K., C.S.M., and J.S. designed and edited manuscript.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

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