Document is current
Any future updates will be listed below
-
Authors
Brynildsen, Julia K.
Fotiadis, Panagiotis
Szymula, Karol P.
Kim, Jason Z.
Pasqualetti, Fabio
Graybiel, Ann M.
Desrochers, Theresa M.
Bassett, Dani S.
-
Funding
Funding for this research was provided by:
National Institute on Alcohol Abuse and Alcoholism (F32-AA030475)
National Institute of Biomedical Imaging and Bioengineering (T32-EB020087)
Cornell Bethe/KIC/Wilkins postdoctoral fellowship
Cornell Neurotech Mong Family Foundation postdoctoral fellowship
Eric and Wendy Schmidt AI in Science postdoctoral fellowship
Army Research Office (W911NF-16-1-0474)
Army Research Office (W911NF-16-1-0474)
National Institute of Neurological Disorders and Stroke (R01-NS025529)
National Institute of Neurological Disorders and Stroke (R01 NS099348)
National Eye Institute (R01-EY012848)
National Institute of Mental Health (R21MH125010)
National Institute of Mental Health (2-R01-DC-009209-11)
National Science Foundation (BCS-2143656)
National Science Foundation (PHY-1554488)
John D. and Catherine T. MacArthur Foundation
Alfred P. Sloan Foundation
ISI Foundation
Paul Allen Foundation
Army Research Laboratory (W911NF-10-2-0022)
National Institute of Child Health and Human Development (1R01HD086888-01)
- License Information
-
More Information
Article History
Received: 9 April 2025
Accepted: 2 December 2025
First Online: 22 January 2026
Competing interests
: The authors declare no competing interests.
: Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minorities are under-cited relative to the number of such papers in the field 134–138 . Here, we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, and other factors. We obtained the predicted gender of the first and last author of each reference by using databases that store the probability of a name being carried by a woman 138,139 . By this measure (and excluding self-citations to the first and last authors of our current paper), our references contain 10.6% woman(first)/woman(last), 5.8% man/woman, 19.2% woman/man, 57.7% man/man, and 6.73% unknown categorization. This method is limited in that (a) names, pronouns, and social media profiles used to construct the databases may not, in every case, be indicative of gender identity and (b) it cannot account for intersex, non-binary, or transgender people. We look forward to future work that could help us to better understand how to support equitable practices in science.
