Confounds in multivariate pattern analysis: Theory and rule representation case study
Confounds in multivariate pattern analysis: Theory and rule representation case study
M. T. Todd,L. Nystrom,J. Cohen
2013 · DOI: 10.1016/j.neuroimage.2013.03.039
NeuroImage · 201 Citations
TLDR
It is demonstrated that widely used approaches to MVPA can systematically admit certain confounds that are appropriately eliminated by GLMA, which raises the question of whether recently reported results truly reflect rule representations, or rather the effects of confounds such as reaction time, difficulty, or other variables of no interest.
