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Recommendations for the responsible use and communication of race and ethnicity in neuroimaging research

Abstract

The growing availability of large-population human biomedical datasets provides researchers with unique opportunities to conduct rigorous and impactful studies on brain and behavioral development, allowing for a more comprehensive understanding of neurodevelopment in diverse populations. However, the patterns observed in these datasets are more likely to be influenced by upstream structural inequities (that is, structural racism), which can lead to health disparities based on race, ethnicity and social class. This paper addresses the need for guidance and self-reflection in biomedical research on conceptualizing, contextualizing and communicating issues related to race and ethnicity. We provide recommendations as a starting point for researchers to rethink race and ethnicity choices in study design, model specification, statistical analysis and communication of results, implement practices to avoid the further stigmatization of historically minoritized groups, and engage in research practices that counteract existing harmful biases.

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References

  1. Laird, A. R. Large, open datasets for human connectomics research: considerations for reproducible and responsible data use. NeuroImage 244, 118579 (2021).

    Article  PubMed  Google Scholar 

  2. Bailey, Z. D. et al. Structural racism and health inequities in the USA: evidence and interventions. Lancet 389, 1453–1463 (2017).

    Article  PubMed  Google Scholar 

  3. Graves, J. L. Jr & Goodman, A. H. Racism, Not Race: Answers to Frequently Asked Questions (Columbia Univ. Press, 2021).

  4. Müller, R. et al. Next steps for global collaboration to minimize racial and ethnic bias in neuroscience. Nat. Neurosci. https://doi.org/10.1038/s41593-023-01369-6 (2023).

  5. Nature. Why Nature is updating its advice to authors on reporting race or ethnicity. Nature 616, 219–219 (2023).

  6. Abiodun, S. J. ‘Seeing color,’ a discussion of the implications and applications of race in the field of neuroscience. Front. Hum. Neurosci. 13, 280 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Girolamo, T., Parker, T. C. & Eigsti, I. -M. Incorporating dis/ability studies and critical race theory to combat systematic exclusion of black, indigenous, and people of color in clinical neuroscience. Front. Neurosci. 16, 988092 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Green, K. H. et al. A perspective on enhancing representative samples in developmental human neuroscience: connecting science to society. Front. Integr. Neurosci. 16, 981657 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Rebello, V. & Uban, K. A. A call to leverage a health equity lens to accelerate human neuroscience research. Front. Integr. Neurosci. 17, 1035597 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ricard, J. A. et al. Confronting racially exclusionary practices in the acquisition and analyses of neuroimaging data. Nat. Neurosci. 26, 4–11 (2023).

    Article  CAS  PubMed  Google Scholar 

  11. Rollins, O. Towards an antiracist (neuro)science. Nat. Hum. Behav. 5, 540–541 (2021).

    Article  PubMed  Google Scholar 

  12. Webb, E. K., Cardenas-Iniguez, C. & Douglas, R. Radically reframing studies on neurobiology and socioeconomic circumstances: a call for social justice-oriented neuroscience. Front. Integr. Neurosci. 16, 958545 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Okun, T. White Supremacy Culture—Still Here https://www.dismantlingracism.org/uploads/4/3/5/7/43579015/okun_-_white_sup_culture.pdf (2021).

  14. Valles, S. Philosophy of Population Health: Philosophy for a New Public Health Era (Routledge, 2018).

  15. Morning, A. Ethnic classification in global perspective: a cross-national survey of the 2000 Census round. Popul. Res. Policy Rev. 27, 239–272 (2008).

    Article  Google Scholar 

  16. Roberts, D. Fatal Invention: How Science, Politics, and Big Business Re-Create Race in the Twenty-First Century (New Press/ORIM, 2011). This book provides a rich account of how racial categories have been created and maintained in the United States, and how they have been used in biomedical research.

  17. Pitts-Taylor, V. Neurobiologically poor? Brain phenotypes, inequality, and biosocial determinism. Sci. Technol. Hum. Values 44, 660–685 (2019).

    Article  Google Scholar 

  18. Rogers, L. O., Niwa, E. Y., Chung, K., Yip, T. & Chae, D. M(ai)cro: centering the macrosystem in human development. Hum. Dev. 65, 270–292 (2021).

    Article  Google Scholar 

  19. Dennis, A. C., Chung, E. O., Lodge, E. K., Martinez, R. A. & Wilbur, R. E. Looking back to leap forward: a framework for operationalizing the structural racism construct in minority and immigrant health research. Ethn. Dis. 31, 301–310 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Goldfarb, M. G. & Brown, D. R. Diversifying participation: the rarity of reporting racial demographics in neuroimaging research. NeuroImage 254, 119122 (2022).

    Article  PubMed  Google Scholar 

  21. Sterling, E., Pearl, H., Liu, Z., Allen, J. W. & Fleischer, C. C. Demographic reporting across a decade of neuroimaging: a systematic review. Brain Imaging Behav. 16, 2785–2796 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Taylor, L. & Rommelfanger, K. S. Mitigating white Western individualistic bias and creating more inclusive neuroscience. Nat. Rev. Neurosci. 23, 389–390 (2022).

    Article  CAS  PubMed  Google Scholar 

  23. Atkin, A. L. et al. Race terminology in the field of psychology: acknowledging the growing multiracial population in the US. Am. Psychol. 77, 381–393 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Balestra, C. & Fleischer, L. Diversity statistics in the OECD: how do OECD countries collect data on ethnic, racial and indigenous identity? OECD https://doi.org/10.1787/89bae654-en (2018).

  25. American Psychological Association. APA Guidelines on Race and Ethnicity in Psychology: Promoting Responsiveness and Equity https://www.apa.org/about/policy/guidelines-race-ethnicity.pdf (2019).

  26. Flanagin, A., Frey, T. & Christiansen, S. L., AMA Manual of Style Committee. Updated guidance on the reporting of race and ethnicity in medical and science journals. JAMA 326, 621–627 (2021).

    Article  PubMed  Google Scholar 

  27. Duggan, C. P., Kurpad, A., Stanford, F. C., Sunguya, B. & Wells, J. C. Race, ethnicity, and racism in the nutrition literature: an update for 2020. Am. J. Clin. Nutr. 112, 1409–1414 (2020).

    Article  PubMed  Google Scholar 

  28. Krieger, N. Structural racism, health inequities, and the two-edged sword of data: structural problems require structural solutions. Front. Public Health 9, 655447 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Saini, A. Superior: the Return of Race Science (Press, 2019).

  30. Zuberi, T. & Bonilla-Silva, E. White Logic, White Methods: Racism and Methodology (Rowman & Littlefield, 2008).

  31. Fan, C. C. et al. Adolescent Brain Cognitive Development (ABCD) study Linked External Data (LED): Protocol and practices for geocoding and assignment of environmental data. Dev. Cogn. Neurosci. 52, 101030 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Cardenas-Iniguez, C. et al. Building towards an adolescent neural urbanome: expanding environmental measures using linked external data (LED) in the ABCD Study. Dev. Cogn. Neurosci. https://doi.org/10.1016/j.dcn.2023.101338 (2024). This article provides a comprehensive review of many variables that can be used to directly measure social and physical environments, instead of using race and ethnicity as proxies.

  33. Gonzalez, M. R. et al. Positive economic, psychosocial, and physiological ecologies predict brain structure and cognitive performance in 9-10-year-old children. Front. Hum. Neurosci. 14, 578822 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Gonzalez, R. et al. An update on the assessment of culture and environment in the ABCD Study: emerging literature and protocol updates over three measurement waves. Dev. Cogn. Neurosci. 52, 101021 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Hoffman, E. A. et al. Stress exposures, neurodevelopment and health measures in the ABCD study. Neurobiol. Stress 10, 100157 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Meredith, W. J., Cardenas-Iniguez, C., Berman, M. G. & Rosenberg, M. D. Effects of the physical and social environment on youth cognitive performance. Dev. Psychobiol. 64, e22258 (2022).

    Article  PubMed  Google Scholar 

  37. Zucker, R. A. et al. Assessment of culture and environment in the Adolescent Brain and Cognitive Development Study: rationale, description of measures, and early data. Dev. Cogn. Neurosci. 32, 107–120 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Benmarhnia, T., Hajat, A. & Kaufman, J. S. Inferential challenges when assessing racial/ethnic health disparities in environmental research. Environ. Health 20, 7 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Johfre, S. S. & Freese, J. Reconsidering the reference category. Sociol. Methodol. 51, 253–269 (2021).

    Article  Google Scholar 

  40. Roberts, D. E. & Rollins, O. Why sociology matters to race and biosocial science. Annu. Rev. Socio. 46, 195–214 (2020).

    Article  Google Scholar 

  41. National Academies of Sciences, Engineering, and Medicine. Using Population Descriptors in Genetics and Genomics Research: a New Framework for an Evolving Field https://doi.org/10.17226/26902 (National Academies Press, 2023). This report summarizes important issues relevant to genetics research and provides concrete recommendations for researchers, including flowcharts, checklists and additional tools for implementation.

  42. Cosgrove, K. T. et al. Limits to the generalizability of resting-state functional magnetic resonance imaging studies of youth: an examination of ABCD Study baseline data. Brain Imaging Behav. https://doi.org/10.1007/s11682-022-00665-2 (2022).

  43. White, E. J. et al. Five recommendations for using large-scale publicly available data to advance health among American Indian peoples: the Adolescent Brain and Cognitive Development (ABCD) StudySM as an illustrative case. Neuropsychopharmacology 48, 263–269 (2023).

    Article  PubMed  Google Scholar 

  44. Gard, A. M., Hyde, L. W., Heeringa, S. G., West, B. T. & Mitchell, C. Why weight? Analytic approaches for large-scale population neuroscience data. Dev. Cogn. Neurosci. 59, 101196 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Lett, E. et al. Health equity tourism: ravaging the justice landscape. J. Med. Syst. 46, 17 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Krieger, N., Boyd, R. W., Maio, F. D. & Maybank, A. Medicine’s privileged gatekeepers: producing harmful ignorance about racism and health. Health Affairs Forefront https://www.healthaffairs.org/do/10.1377/forefront.20210415.305480 (2021).

  47. Braveman, P. Health disparities and health equity: concepts and measurement. Annu. Rev. Public Health 27, 167–194 (2006).

    Article  PubMed  Google Scholar 

  48. Braveman, P., Arkin, E., Orleans, T., Proctor, D. & Plough, A. What is health equity? And what difference does a definition make? The Equity Initiative https://resources.equityinitiative.org/handle/ei/418 (2017).

  49. Ford, C. L. & Airhihenbuwa, C. O. Critical race theory, race equity, and public health: toward antiracism praxis. Am. J. Public Health 100, S30–S35 (2010). This article provides a framework for applying concepts of CRT to empirical studies in public health, and other fields focusing on human research.

  50. Ford, C. L. & Airhihenbuwa, C. O. The public health critical race methodology: praxis for antiracism research. Soc. Sci. Med. 71, 1390–1398 (2010).

    Article  PubMed  Google Scholar 

  51. Ford, C. L. & Airhihenbuwa, C. O. Commentary: just what is critical race theory and what’s it doing in a progressive field like public health? Ethn. Dis. 28, 223–230 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Katikireddi, S. V. & Valles, S. A. Coupled ethical–epistemic analysis of public health research and practice: categorizing variables to improve population health and equity. Am. J. Public Health 105, e36–e42 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Tuana, N. in Scientific Integrity and Ethics in the Geosciences (ed. Gunderson, L. C.) 155–173 (American Geophysical Union, 2017).

  54. Valles, S. A., Piso, Z. & O’Rourke, M. Coupled ethical-epistemic analysis as a tool for environmental science. Ethics Policy Environ. 22, 267–286 (2019).

    Article  Google Scholar 

  55. Causadias, J. M., Vitriol, J. A. & Atkin, A. L. Do we overemphasize the role of culture in the behavior of racial/ethnic minorities? Evidence of a cultural (mis)attribution bias in American psychology. Am. Psychol. 73, 243–255 (2018).

    Article  PubMed  Google Scholar 

  56. Szanton, S. L., LaFave, S. E. & Thorpe, R. J. Jr. Structural racial discrimination and structural resilience: measurement precedes change. J. Gerontol. Ser. A 77, 402–404 (2022).

    Article  Google Scholar 

  57. La Scala, S., Mullins, J. L., Firat, R. B.; Emotional Learning Research Community Advisory Board & Michalska, K. J. Equity, diversity, and inclusion in developmental neuroscience: practical lessons from community-based participatory research. Front. Integr. Neurosci. 16, 1007249 (2023).

  58. Randolph, A. C. et al. Creating a sustainable action-oriented engagement infrastructure—a UMN-MIDB perspective. Front. Integr. Neurosci. 16, 1060896 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Shalowitz, M. U. et al. Community-based participatory research: a review of the literature with strategies for community engagement. J. Dev. Behav. Pediatr. 30, 350–361 (2009).

    Article  PubMed  Google Scholar 

  60. Buchanan, N. T. & Wiklund, L. O. Why clinical science must change or die: integrating intersectionality and social justice. Women Ther. 43, 309–329 (2020).

    Article  Google Scholar 

  61. Settles, I. H., Warner, L. R., Buchanan, N. T. & Jones, M. K. Understanding psychology’s resistance to intersectionality theory using a framework of epistemic exclusion and invisibility. J. Soc. Issues 76, 796–813 (2020).

    Article  Google Scholar 

  62. Bodison, S. C., Nagel, B., Lopez, D. A., Huber, R. & Members of ABCD JEDI WG3. Equity-focused questions for researchers using the ABCD Study. OSF Home https://doi.org/10.17605/OSF.IO/PM7SY (2023).

  63. Carrero Pinedo, A., Caso, T. J., Rivera, R. M., Carballea, D. & Louis, E. F. Black, indigenous, and trainees of color stress and resilience: the role of training and education in decolonizing psychology. Psychol. Trauma Theory Res. Pract. Policy 14, S140–S147 (2022).

    Article  Google Scholar 

  64. Rodriguez-Seijas, C. A. et al. The next generation of clinical psychological science: moving toward antiracism. Clin. Psychol. Sci. https://doi.org/10.1177/21677026231156545 (2023).

  65. Buchanan, N. T., Perez, M., Prinstein, M. J. & Thurston, I. B. Upending racism in psychological science: strategies to change how science is conducted, reported, reviewed, and disseminated. Am. Psychol. 76, 1097–1112 (2021).

    Article  PubMed  Google Scholar 

  66. Garcini, L. M. et al. Increasing diversity in developmental cognitive neuroscience: a roadmap for increasing representation in pediatric neuroimaging research. Dev. Cogn. Neurosci. 58, 101167 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Roberts, S. O., Bareket-Shavit, C., Dollins, F. A., Goldie, P. D. & Mortenson, E. Racial inequality in psychological research: trends of the past and recommendations for the future. Perspect. Psychol. Sci. 15, 1295–1309 (2020).

    Article  PubMed  Google Scholar 

  68. Bryant, B. E., Jordan, A. & Clark, U. S. Race as a social construct in psychiatry research and practice. JAMA Psychiatry 79, 93–94 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Roth, W. D. The multiple dimensions of race. Ethn. Racial Stud. 39, 1310–1338 (2016).

    Article  Google Scholar 

  70. Ford, C. L. & Harawa, N. T. A new conceptualization of ethnicity for social epidemiologic and health equity research. Soc. Sci. Med. 71, 251–258 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Delgado, R. & Stefancic, J. Critical Race Theory: an Introduction (NYU Press, 2012).

  72. Ray, V. On Critical Race Theory: Why it Matters & Why You Should Care (Random House, 2023).

  73. Kaplan, J. B. & Bennett, T. Use of race and ethnicity in biomedical publication. JAMA 289, 2709–2716 (2003).

    Article  PubMed  Google Scholar 

  74. Mir, G. et al. Principles for research on ethnicity and health: the Leeds Consensus Statement. Eur. J. Public Health 23, 504–510 (2013). This paper outlines the process through which the Leeds Consensus Statement, an international set of recommendations for ethnicity in research, was developed.

  75. Bowleg, L. ‘The master’s tools will never dismantle the master’s house’: ten critical lessons for black and other health equity researchers of color. Health Educ. Behav. 48, 237–249 (2021).

    Article  PubMed  Google Scholar 

  76. Hardeman, R. R., Homan, P. A., Chantarat, T., Davis, B. A. & Brown, T. H. Improving the measurement of structural racism to achieve antiracist health policy. Health Aff. 41, 179–186 (2022).

    Article  Google Scholar 

  77. Lett, E., Asabor, E., Beltrán, S., Cannon, A. M. & Arah, O. A. Conceptualizing, contextualizing, and operationalizing race in quantitative health sciences research. Ann. Fam. Med. 20, 157–163 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  78. López, N., Erwin, C., Binder, M. & Chavez, M. J. Making the invisible visible: advancing quantitative methods in higher education using critical race theory and intersectionality. Race Ethn. Educ. 21, 180–207 (2018).

    Article  Google Scholar 

  79. Nketia, J., Amso, D. & Brito, N. H. Towards a more inclusive and equitable developmental cognitive neuroscience. Dev. Cogn. Neurosci. 52, 101014 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Gillborn, D., Warmington, P. & Demack, S. QuantCrit: education, policy, ‘big data’ and principles for a critical race theory of statistics. Race Ethn. Educ. 21, 158–179 (2018).

    Article  Google Scholar 

  81. Crossing, A. E., Gumudavelly, D., Watkins, N., Logue, C. & Anderson, R. E. A critical race theory of psychology as praxis: proposing and utilizing principles of PsyCrit. J. Adolesc. Res. https://doi.org/10.1177/07435584221101930 (2022).

  82. Martín-Baró, I. Writings for a Liberation Psychology (Harvard Univ. Press, 1994).

  83. Omi, M. & Winant, H. Racial Formation in the United States: From the 1960s to the 1980s (Routledge & Kegan Paul, 1986).

  84. Feagin, J. R. & Ducey, K. Racist America: Roots, Current Realities, and Future Reparations (Routledge, 2018).

  85. Williams, D. R. & Sternthal, M. Understanding racial-ethnic disparities in health: sociological contributions. J. Health Soc. Behav. 51, S15–S27 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Haeny, A. M., Holmes, S. C. & Williams, M. T. The need for shared nomenclature on racism and related terminology in psychology. Perspect. Psychol. Sci. 16, 886–892 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Bonilla-Silva, E. Rethinking racism: toward a structural interpretation. Am. Sociol. Rev. 62, 465–480 (1997).

    Article  Google Scholar 

  88. Chen, J. & Courtwright, A. in Encyclopedia of Global Bioethics (ed. ten Have, H.) 2706–2712 (Springer International Publishing, Cham, 2016).

  89. Garavan, H. et al. Recruiting the ABCD sample: design considerations and procedures. Dev. Cogn. Neurosci. 32, 16–22 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Jernigan, T. L., Brown, S. A. & Dowling, G. J. The Adolescent Brain Cognitive Development Study. J. Res. Adolesc. 28, 154–156 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Compton, W. M., Dowling, G. J. & Garavan, H. Ensuring the best use of data: the Adolescent Brain Cognitive Development Study. JAMA Pediatr. 173, 809–810 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Dick, A. S. et al. Meaningful associations in the adolescent brain cognitive development study. NeuroImage 239, 118262 (2021).

    Article  PubMed  Google Scholar 

  93. Hoffman, E. A., LeBlanc, K., Weiss, S. R. B. & Dowling, G. J. Transforming the future of adolescent health: opportunities from the Adolescent Brain Cognitive Development Study. J. Adolesc. Health 70, 186–188 (2022).

    Article  PubMed  Google Scholar 

  94. Simmons, C. et al. Responsible use of open-access developmental data: The Adolescent Brain Cognitive Development (ABCD) Study. Psychol. Sci. https://doi.org/10.1177/09567976211003564 (2021).

  95. Telles, E. Latinos, race, and the U.S. census. Ann. Am. Acad. Pol. Soc. Sci. 677, 153–164 (2018).

    Article  Google Scholar 

  96. Garcia, N. M., López, N. & Vélez, V. N. QuantCrit: rectifying quantitative methods through critical race theory. Race Ethn. Educ. 21, 149–157 (2018).

    Article  Google Scholar 

  97. Tabron, L. A. & Thomas, A. K. Deeper than wordplay: a systematic review of critical quantitative approaches in education research (2007–2021). Rev. Educ. Res. https://doi.org/10.3102/00346543221130017 (2023).

  98. Suzuki, S., Morris, S. L. & Johnson, S. K. Using QuantCrit to advance an anti-racist developmental science: applications to mixture modeling. J. Adolesc. Res. 36, 535–560 (2021). This article provides a review of the QuantCrit literature and provides recommendations that researchers can use when conducting antiracism-focused quantitative research.

    Article  Google Scholar 

  99. Castillo, W. & Gillborn, D. How to ‘QuantCrit:’ practices and questions for education data researchers and users. EdWorkingPapers https://www.edworkingpapers.com/ai22-546 (2022).

  100. Roberts, S. O. & Mortenson, E. Challenging the white = neutral framework in psychology. Perspect. Psychol. Sci. https://doi.org/10.1177/17456916221077117 (2022).

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Acknowledgements

We thank the large number of people who provided feedback, comments and critiques over the development of this paper. In particular, we thank the members of the ABCD Study JEDI Working Groups, who provided many of the initial discussions that led to the development of this paper. We particularly acknowledge the following people for providing numerous comments on drafts of this manuscript: M. Herting, K. Bagot, L. Uddin, S. Bodison, R. Huber, D. Lopez, E. Hoffman, S. Adise, A. Potter and K. Uban. C.C.-I. acknowledges fellow NSP (R25NS089462), BRAINS (R25NS094094) and Diversifying CNS (R25NS117356) scholars, who have provided invaluable support and inspiration for addressing structural barriers in neuroscience for BIPOC scholars, as well as T32ES013678, R25DA059073, and R25MH125545. C.C.-I. is supported by National Institute of Environmental Health Science grants T32ES013678, R01ES031074 and P30ES007048, and National Institute on Minority Health and Health Disparities grant P50MD015705. M.R.G. is supported by National Institute on Alcohol Abuse and Alcoholism grant K01AA030325 and National Institute on Drug Abuse grants R61DA058976, R25DA050724, and R25DA050687.

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C.C.-I. wrote the first draft of the manuscript. M.R.G. wrote sections of the manuscript. All authors contributed to the revision of the paper and approved the submitted version.

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Correspondence to Carlos Cardenas-Iniguez.

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Cardenas-Iniguez, C., Gonzalez, M.R. Recommendations for the responsible use and communication of race and ethnicity in neuroimaging research. Nat Neurosci 27, 615–628 (2024). https://doi.org/10.1038/s41593-024-01608-4

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