Functions to analyze Classification Images
DEMOSTAT4CI illustrates the usage of the Stat2Ci toolbox on two classification images from: Gosselin, F. & Schyns, P. G. (2001). Bubbles: A technique to reveal the use of information in recognition. Vision Research, 41, 2261-2271. The Stat4Ci toolbox allows to perform the Pixel and the Cluster tests, both based on Random Field Theory. These tests are easy to apply, requiring a mere four pieces of information; and they typically produce statistical thresholds (or p-values) lower than the standard Bonferroni correction.
An excellent non-technical reference is: K. J. Worsley (1996) the geometry of random image. Chance, 9, 27-40.
We borrowed from several sources: the STAT_THRESHOLD function was written by Keith Worsley for the fmristat toolbox
(http://www.math.mcgill.ca/~keith/fmristat); and our DISPLAYCI function calls many functions from the
Image Processing toolbox.
The Stat4Ci toolbox is free if you use it in your research, please, cite us: Chauvin, A., Worsley, K. J., Schyns, P. G., Arguin, M. & Gosselin, F. (2005). Accurate statistical test for smooth classification images; Journal of Vision, 5(1), doi:https://doi.org/10.1167/5.9.1
Alan Chauvin ([email protected]) & Frédéric Gosselin ([email protected]), 20/08/2004