18 citations · 23 across the 4 of their papers we have counts for
4 papers
SIMBA: Scalable Image Modeling using a Bayesian Approach, A Consistent Framework for Including Spatial Dependencies in fMRI Studies
Yuan Zhong, Gang Chen, Paul A. Taylor +1
Bayesian spatial modeling provides a flexible framework for whole-brain fMRI analysis by explicitly incorporating spatial dependencies, overcoming the limitations of traditional ma…
Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation
Paul A. Taylor, Himanshu Aggarwal, Peter Bandettini +39
Visualizations are vital for communicating scientific results. Historically, neuroimaging figures have only depicted regions that surpass a given statistical threshold. This practi…
Processing, evaluating and understanding FMRI data with afni_proc.py
Richard C. Reynolds, Daniel R. Glen, Gang Chen +3
FMRI data are noisy, complicated to acquire, and typically go through many steps of processing before they are used in a study or clinical practice. Being able to visualize and und…
False Discovery Rate and Localizing Power
Anderson M. Winkler, Paul A. Taylor, Thomas E. Nichols +1
False discovery rate (FDR) is commonly used for correction for multiple testing in neuroimaging studies. However, when using two-tailed tests, making directional inferences about t…