MRI Analysis, Now With Open Science
It’s fabulous to see yet one more research field, MRI and fMRI, jumping on board with Open Science. The Workshop runs 13-17 December, 2021, and the site is here.
Recall the dead salmon? (tiny.cc/deadsalmon, ITNS p. 485.) Back then, in 2009, a common way to analyse fMRI data relied on p values for each of many thousands of voxels. Apply this analysis to a dead salmon shown two different types of pictures and find part of its (totally dead) nervous system lit up on the analysis screen! It was a massive Type I error, of course, caused by inadequate correction of p values given by the gazillion voxel comparisons. Make a more appropriate correction and all we see is noise. The study deserved its 2012 IgNobel Prize.
Analysis of MRI data has come a long way since 2009, partly prompted by the dead salmon. More recent discussions, for example here and here, include consideration of the basic Open Science issues, including p-hacking, cherry-picking, unplanned analyses, and lack of replication.
The Timetable (Program)
It’s here. Near the top, select your timezone. There are sessions around the 24 hours, grouped to fit the waking hours in Atlantic, Pacific, Indian, and Caribbean zones. It looks to me like a wonderfully broad take on Open Science and Reproducibility. I recognised only a few of the presenters, including:
Valentin Amrhein: P-values and the replicability of results
Brian Nosek: Publishing and Sharing Open Science
I’m giving a brief (20 min, including Q+A) talk: The new statistics for reproducible science in a session titled Study design and interpretation. The reproducibility crisis, running 11.00 to 13.00 on 15 Dec, those times being UTC+11, which includes Sydney and Melbourne. I’ll post my slides in due course.