OHBM 2023 Talks & Posters

Slides available here for Mandy's keynote on "Rethinking scrubbing in fMRI from a statistical perspective".  fMRIscrub package available on Github and CRAN

Github repo for the course: https://github.com/wdweeda/ohbm2023_edu_course/ 

Materials for Mandy's lecture on spatial Bayesian models for powerful task fMRI analysis: Slides and code available hereBayesfMRI R package on GitHub and CRAN.

This talk is based on the following papers:

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

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 

Access slides for Mandy's talk on "Discovering individual functional topology without hours of data"

Check out our posters!

Poster 536

Access the full paper:
Parlak F, Phạm DĐ, 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   

Poster 797

Access the full paper:
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