Confounds in multivariate pattern analysis: Theory and rule representation case study

By Michael T. Todd, Leigh E. Nystrom, J. Cohen. 2013

201 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Social Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Bernhard Schölkopf
2. Moritz Grosse-Wentrup
3. John-Dylan Haynes
4. James V. Haxby
5. Martin N. Hebart
6. Nikolaus Kriegeskorte
7. Pamela K. Douglas
8. Russell A. Poldrack

In Computer Vision and Pattern Recognition

1. John-Dylan Haynes
2. Moritz Grosse-Wentrup
3. Tonio Ball
4. Bernhard Schölkopf
5. Sebastian Weichwald
6. Luc Van Gool
7. Arthur Gretton
8. Dacheng Tao

In Social Psychology

1. John-Dylan Haynes
2. Bernhard Schölkopf
3. Nikolaus Weiskopf
4. Tania Singer

Citations in the corpus

• Causal and anti-causal learning in pattern recognition for neuroimaging (2015, background): “Decoding models, on the other hand, may determine brain state features as relevant that are statistically independent of the experimental condition [2].”
• A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives. (2015, background): “Two solutions are to either regress out the nuisance variable (Todd et al., 2013; Woolgar et al., 2014), or to directly compare decoding for nuisance variables and for the cognitive factor of interest (Wisniewski et al., 2014).”