Working Papers & Preprints

Butler ER, Samia N, Mejia AF, Pham DD, Pines A, and Nusslock R. Sex differences in response to violence: Role of salience network expansion and connectivity on depression. Under review. https://doi.org/10.21203/rs.3.rs-5822551/v1

Mejia AF, Bolin D, Spencer D, and Eloyan A. Accurate estimation of functional brain connectivity via Bayesian ICA with population-derived priors. Major revision.

Parlak F, Pham DD, Mejia AF. A robust multivariate, non-parametric outlier identification method for scrubbing in fMRI. https://arxiv.org/abs/2304.14634 

Spencer D, Bolin D, Nebel MB and Mejia AF. Fast Bayesian estimation of brain activation with cortical surface and subcortical data using expectation-maximization.  https://arxiv.org/abs/2203.00053  

Published & Accepted Work

2025

Derman D, Pham DD, Mejia AF and Ferradal SL. Individual patterns of functional connectivity in neonates as revealed by surface-based Bayesian modeling.  Imaging Neuroscience (2025). https://doi.org/10.1162/imag_a_00504 

2024

Hayashi S, Caron B, [30 others] and Pestilli F. brainlife.io: A decentralized and open source cloud platform to support neuroscience research. Nature Methods (2024). https://www.nature.com/articles/s41592-024-02237-2 

2023

Koppelmans V,  Ruitenberg M, Shaefer SY, King JB, Hoffman JM, Mejia AF,  Tasdizen T, and Duff K.  Worse Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification. Journal of Alzheimer’s Disease (2023). https://dx.doi.org/10.3233/JAD-221297 

Phạm DĐ, McDonald DJ, Ding L, Nebel MB, Mejia AF. Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing. NeuroImage (2023). https://doi.org/10.1016/j.neuroimage.2023.119972 

Taylor PA, Reynolds RC, Calhoun V, Gonzalez-Castillo J, Handwerker DA, Bandettini PA, Mejia AF, Chen G. Highlight Results, Don't Hide Them: Enhance interpretation, reduce biases and improve reproducibility. NeuroImage (2023). https://doi.org/10.1016/j.neuroimage.2023.120138 

Parlak F, Pham DD, Spencer D, Welsh RC and Mejia AF. Sources of Residual Autocorrelation in Multiband Task fMRI and Strategies for Effective Mitigation. Frontiers in Neuroscience (2023). https://doi.org/10.3389/fnins.2022.1051424  

2022

Noble S, Mejia AF, Zalesky A, Scheinost D. Improving power in fMRI by moving beyond cluster-level inference. Proceedings of the National Academy of Science (2022). https://www.pnas.org/doi/10.1073/pnas.2203020119 

Gaddis A*, Lidstone DE*, Nebel MB, Griffiths R, Mostofsky SH, Mejia AF, Barrett F.  Psilocybin induces spatially constrained alterations in thalamic functional organization and connectivity. NeuroImage (2022) https://doi.org/10.1016/j.neuroimage.2022.119434 

Mejia AF, Bolin D, Yue Y, Wang J, Caffo BS and Nebel MB. A spatial template independent component analysis model for subject-level brain network estimation and inference. Journal of Computational and Graphical Statistics (2022).  https://doi.org/10.1080/10618600.2022.2104289 

Mejia AF, Koppelmans V, Jelsone-Swain L, Kalra S, and Welsh RC. Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS. NeuroImage (2022). https://doi.org/10.1016/j.neuroimage.2022.119180 

Pham DD, Muschelli J and Mejia AF. ciftiTools: A package for reading, writing, visualizing and manipulating CIFTI files in R. NeuroImage (2022). https://doi.org/10.1016/j.neuroimage.2022.118877 

Spencer D, Yue YR, Bolin D, Ryan S and Mejia AF. Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups. NeuroImage (2022). https://doi.org/10.1016/j.neuroimage.2022.118908

2021

Mejia AF. Discussion on “Distributional independent component analysis for diverse neuroimaging modalities” by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo. Biometrics (2021). https://doi.org/10.1111/biom.13592 

2020

Murphy MC*, Mejia AF*, Mejia J*, Yan X*, [20 others], Mabry PL**, Ressl S**, Diekman A** and Pestilli F**. Open Science, Communal Culture, and Women’s Participation in the Movement to Improve Science. Proceedings of the National Academy of Science 117.39 (2020): 24154-24164. https://doi.org/10.1073/pnas.1921320117 

Mejia AF, Nebel MB, Wang Y, Caffo BS and Guo Y. Template ICA: Targeted and reliable estimation of subject-level brain networks using big data population priors. Journal of the American Statistical Association 115.531 (2020): 1151-1177. https://doi.org/10.1080/01621459.2019.1679638 

Mejia AF,* Yue Y*, Bolin D, Lindgren F, Lindquist MA. A Bayesian general linear modeling approach to cortical surface fMRI data analysis. Journal of the American Statistical Association (2020): 501-520. https://doi.org/10.1080/01621459.2019.1611582 

2019

Mejia JM, Mejia AF, Pestilli F. Open data on industry payments to healthcare providers reveals potential hidden costs to the public. Nature Communications 10.1 (2019): 1-8. https://doi.org/10.1038/s41467-019-12317-z 

2018

Mejia AF, Nebel MB, Barber AD, Choe AS, Pekar JJ, Caffo B and Lindquist MA. Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. NeuroImage 172 (2018): 478-491. https://doi.org/10.1016/j.neuroimage.2018.01.029 

2017

Mejia AF, Nebel MB, Eloyan A, Caffo B and Lindquist MA.  PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data. Biostatistics 18.3 (2017): 521-536. https://doi.org/10.1093/biostatistics/kxw050 

Webb-Vargas Y, Chen S, Fisher AJ, Mejia AF, Xu Y, Crainiceanu CM, Caffo B and Lindquist MA.  Big data and Neuroimaging. Statistics in Biosciences 9.2 (2017): 543–558. https://doi.org/10.1007/s12561-017-9195-y 

2016

Mejia AF, Sweeney EM, Dewey B, Nair G, Sati P, Shea C, Reich D and Shinohara RT. Statistical estimation of T1 relaxation time using conventional magnetic resonance imaging.  NeuroImage 113 (2016): 176-188. https://doi.org/10.1016/j.neuroimage.2015.12.037 

Pomann GM, Staicu AM, Lobaton E, Mejia AF, Dewey B, Reich DS, Sweeney E and Shinohara R.  A lag functional linear model for prediction of magnetization transfer ratio in multiple sclerosis lesions. Annals of Applied Statistics 10.4 (2016): 2325-2348. https://doi.org/10.1214/16-AOAS981 

Suttner LH, Mejia AF, Dewey B, Sati P, Reich DS and Shinohara RT. Statistical estimation of white matter microstructure from conventional MRI. NeuroImage: Clinical, 12 (2016): 615-623. https://doi.org/10.1016/j.nicl.2016.09.010 

Paik J, Wigley FM, Mejia AF, Hummers LK.  Independent Association of Severity of Muscle Weakness with Disability as Measured by the Health Assessment Questionnaire Disability Index in Scleroderma. Arthritis Care and Research 68.11 (2016): 1695–1703. https://doi.org/10.1002/acr.22870 

2015

Mejia AF, Nebel MB, Shou H, Crainiceanu CM, Pekar JJ, Mostofsky SH, Caffo B and Lindquist MA. Improving reliability of subject-level resting-state fMRI parcellations with shrinkage. NeuroImage 112 (2015): 14-29. https://doi.org/10.1016/j.neuroimage.2015.02.042 

Lindquist MA and Mejia AF. Zen and the art of multiple comparisons. Psychosomatic Medicine 77.2 (2015): 114-125. https://doi.org/10.1097/PSY.0000000000000148 

2014

Shou H, Eloyan A, Nebel MB, Mejia AF, Pekar JJ, Mostofsky S, Caffo B, Lindquist MA and Crainiceanu, CM. Shrinkage prediction of seed-voxel brain connectivity using resting-state fMRI. NeuroImage (2014). https://doi.org/10.1016/j.neuroimage.2014.05.043 

Peterson D, Rajneesh M, Crocetti D, Mejia AF, Mostofsky SH. Left-hemispheric microstructural abnormalities in children with high functioning Autism Spectrum Disorder. Autism Research (2014). https://doi.org/10.1002/aur.1413 

Ament K, Mejia AF, Buhlman R, Erklin S, Caffo B, Mostofsky S, & Wodka E. Evidence for specificity of motor impairments in catching and balance in children with autism. Journal of Autism and Developmental Disorders (2014): 1-10. https://dx.doi.org/10.1007%2Fs10803-014-2229-0 

* indicates shared first authorship
** indicates shared senior authorship