What is a representative brain? Neuroscience meets population science
Open accessAbstract
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.
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Neuroscience research has historically largely reflected small and homogeneous samples of participants and has had limited ability to integrate social context into its protocols.
“Neuroscience research has historically largely reflected small and homogeneous samples of participants and has had limited ability to integrate social context into its protocols (Falk et al., 2013).”
From The role (and limits) of developmental neuroscience in determining adolescents' autonomy rights: The case for reproductive and voting rights (2024) · cites this paper as Falk et al., 2013
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“Neuroscience research has historically largely reflected small and homogeneous samples of participants and has had limited ability to integrate social context into its protocols (Falk et al., 2013).”
Self-citationThe Personal Data Is Political
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- Authors
- Falk, E. B., Hyde, L. W., Mitchell, C., Faul, J., Gonzalez, R., Heitzeg, M. M., Keating, D. P., Langa, K. M., Martz, M. E., Maslowsky, J., Morrison, F. J., Noll, D. C., Patrick, M. E., Pfeffer, F. T., Reuter-Lorenz, P. A., Thomason, M. E., Davis-Kean, P., Monk, C. S., & Schulenberg, J.
- Affiliations
- University of Pennsylvania (US)
- University of Michigan (US)
- Psychology,
- Psychiatry,
- VA Center for Clinical Management Research (US)
- University of Wisconsin–Madison (US)
- Biomedical Engineering;
- Survey Research Center, and
- Institute for Social Research (NO)
- National Institutes of Health (US)
- ORCID
- Falk, Emily B.
- Hyde, Luke W.
- Mitchell, Colter
- Faul, Jessica
- Gonzalez, Richard
- Heitzeg, Mary M.
- Keating, Daniel P.
- Langa, Kenneth M.
- Martz, Meghan E.
- Maslowsky, Julie
- Morrison, Frederick J.
- Noll, Douglas C.
- Patrick, Megan E.
- Pfeffer, Fabian T.
- Thomason, Moriah E.
- Davis-Kean, Pamela
- Monk, Christopher S.
- Schulenberg, John
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-10-22
- Volume
- 110
- Issue
- 44
- Pages
- 17615-17622
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3816464
- OpenAlex
- W2118518216
- Cited by
- 265
- References
- 131
- Citations by year
- 2026: 24 · 2025: 18 · 2024: 33 · 2023: 25 · 2022: 29 · 2021: 18 · 2020: 32 · 2019: 14 · 2018: 24 · 2017: 11 · 2016: 15 · 2015: 16 · 2014: 5 · 2013: 1
- FWCI
- 1.06
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- ScholarlyCommons (University of Pennsylvania) (submittedVersion)
- Funders
- National Institutes of Health (7dp2da035156-02)
- National Institute on Alcohol Abuse and Alcoholism (R01AA012217)
- National Institute on Aging (U01 AG 09740, U01AG009740)
- National Institute on Drug Abuse (DP2DA035156-01, DP2 DA035156, R01DA027261)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- sample representativeness, individual differences, generalizability of findings, neural mechanisms, interdisciplinary neuroscience, social demography, population science
- MeSH terms
- Humans, Individuality, Interpersonal Relations, Neurosciences, Interdisciplinary Communication, Neuroimaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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