Racial and ethnic disparities in fMRI head motion exclusion
Presented During: Poster Session 3
Friday, June 27, 2025: 01:45 PM - 03:45 PM
Friday, June 27, 2025: 01:45 PM - 03:45 PM
Presented During: Poster Session 4
Saturday, June 28, 2025: 01:45 PM - 03:45 PM
Saturday, June 28, 2025: 01:45 PM - 03:45 PM
Poster No:
1589
Submission Type:
Abstract Submission
Authors:
Jocelyn Ricard1, Eric Bridgeford1, Keith Humphreys1, Russell Poldrack1
Institutions:
1Stanford University, Stanford, CA
First Author:
Co-Author(s):
Introduction:
Head motion during functional magnetic resonance imaging (fMRI) scans is a significant challenge in neuroimaging research, often leading to data quality issues and participant exclusions especially among pediatric and clinical populations (Greene et al., 2016). Head motion exclusions in MRI studies, while necessary for ensuring data quality, may inadvertently introduce biases by disproportionately excluding certain sociodemographic groups (Teo et al., 2024, Cosgrove et al., 2022).
Methods:
Using data from the Adolescent Brain Cognitive Development (ABCD) study (n=11,874), we investigated racial and ethnic disparities in participant exclusions due to high head motion (mean framewise displacement [FD] ≥ 0.5mm). We performed logistic regression analysis and conducted pairwise comparisons of exclusion rates across racial/ethnic groups using Holm-corrected p-values.
Results:
The analysis revealed significant associations between race/ethnicity and exclusion due to head motion. Black participants had nearly twice the odds of exclusion compared to White participants (Odds Ratio [OR] = 1.99, 95% CI [1.75, 2.28], z = 10.13, p < 0.0001), followed by Hispanic participants (OR = 1.33, 95% CI [1.17, 1.51], z = 4.53, p < 0.0001). Participants racially/ethnically identifying as "Other" had significantly higher odds of exclusion (OR = 1.26, 95% CI [1.07, 1.49], z = 2.72, p = 0.006), while Asian participants showed no significant difference in exclusion rates (OR = 1.14, 95% CI [0.80, 1.63], z = 0.74, p = 0.458). Holm-corrected pairwise comparisons revealed that Black participants were excluded at significantly higher rates than Hispanic (z = 6.94, p < 0.0001), Other (z = 6.40, p < 0.0001), and Asian (z = 4.02, p = 0.0003) participants. No significant differences were found between Hispanic, Other, and Asian groups.
Conclusions:
These results highlight the disproportionate exclusion of Black and Hispanic participants, raising concerns about the generalizability of neuroimaging research. Exclusion criteria based on head motion may inadvertently introduce sampling bias. While motion distortion and artifact correction are crucial for data quality, these practices may conflict with efforts to include groups that are disproportionately affected by current exclusion criteria within neuroimaging research (Ricard et al., 2023).
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Motion Correction and Preprocessing 1
Keywords:
FUNCTIONAL MRI
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Provide references using APA citation style.
2. Teo, T. W. J., Saffari, S. E., Chan, L. L., & Welton, T. (2024). Comparison of MRI head motion indicators in 40,969 subjects informs neuroimaging study design. Scientific Reports, 14(1), 29430.
3. Cosgrove KT, McDermott TJ, White EJ, Mosconi MW, Thompson WK, Paulus MP, et al. (2022): Limits to the generalizability of resting-state functional magnetic resonance imaging studies of youth: An examination of ABCD Study® baseline data. Brain Imaging and Behavior 16: 1919–1925.
4. Ricard JA, Parker TC, Dhamala E, Kwasa J, Allsop A, Holmes AJ (2023): Confronting racially exclusionary practices in the acquisition and analyses of neuroimaging data. Nat Neurosci 26: 4–11.