Link to Google Scholar here; software toolboxes are on github here.

1. Miranda, M. F. (2024). A canonical polyadic tensor basis for fast Bayesian estimation of multi-subject fMRI activation patterns. Frontiers in Neuroinformatics, 18, 1399391.

2. Miranda, M. F. (2024). Analysis methods for functional connectivity: from seed-regions to data-driven approaches. In Rocca, M. & Filippi, M. (Eds.), Functional Connectivity of the Human Brain. Elsevier. Accepted for publication.

3. Shahosenni, Y., Beaulac, C., Nathoo, F. S., & Miranda, M. F. (2024). Characterizing brain function in ADHD through a spatially-varying Bayesian model for the long-memory parameter in rs-fMRI. In preparation.

4. Miranda, M. F., & Morris, J. S. (2024). Novel Bayesian method for simultaneous detection of activation signatures and background connectivity for task fMRI data. Preprint available at https://arxiv.org/abs/2109.00160. Under review.

5. Beaulac, C., Wu, S., Gibson, E., Miranda, M. F., Cao, J., Rocha, L., Beg, M. F., & Nathoo, F. S. (2023). Neuroimaging feature extraction using a neural network classifier for imaging genetics. BMC Bioinformatics, 24, 271. https://doi.org/10.1186/s12859-023-05394-x

6. Shahosenni, Y., & Miranda, M. F. (2022). Functional connectivity methods and their applications in fMRI data. Entropy, 24, 390. https://doi.org/10.3390/e24030390

7. Wei, Z., Yang, A., Rocha, L., Miranda, M. F., & Nathoo, F. (2022). A review of Bayesian hypothesis testing and its practical implementation. Entropy, 24, 161. https://doi.org/10.3390/e24020161

8. Rangel, M. L., Souza, L., Rodrigues, L. C., Oliveira, J. M., Miranda, M. F., Galves, A., & Vargas, C. D. (2021). Predicting upcoming events occurring in the space surrounding the hand. Neural Plasticity, Article ID 6649135. https://doi.org/10.1155/2021/6649135

9. Turner, D., Miranda, M. F., Morris, J. S., Girkin, C., & Downs, J. C. (2019). Stress response in intraocular pressure (IOP) in nonhuman primates using continuous IOP telemetry. Ophthalmology Glaucoma, 2(4), 210-214. https://doi.org/10.1016/j.ogla.2019.03.010

10. Lee, W., Miranda, M. F., Veerabhadran, B., Rausch, P., Fazio, M., Downs, J. C., & Morris, J. S. (2018). Bayesian semiparametric functional mixed models for serially correlated functional data, with application to glaucoma data. Journal of the American Statistical Association, 114(526), 495–513.

11. Miranda, M. F., Zhu, H., & Ibrahim, J. G. (2018). TPRM: Tensor partition regression models with applications in imaging biomarker detection. The Annals of Applied Statistics, 12(3), 1422-1450. https://doi.org/10.1214/17-AOAS1116

12. Fraiman, D., Miranda, M. F., Erthal, F., Buur, P. F., Elschot, M., Souza, L., Rombouts, S. A. R. B., van Osch, M. J. P., Schimmelpenninck, C. A., Norris, D. G., Malessy, M. J. A., Galves, A., & Vargas, C. D. (2016). Reduced functional connectivity within the primary motor cortex of patients with brachial plexus injury. NeuroImage: Clinical, 12, 277-284. https://doi.org/10.1016/j.nicl.2016.07.008

13. Miranda, M. F., Zhu, H., & Ibrahim, J. G. (2013). Bayesian spatial transformation models with applications in neuroimaging data. Biometrics, 69(4), 1074-1083. https://doi.org/10.1111/biom.12085