Accurate statistical tests for smooth classification images

被引：159

作者：

Chauvin, A

Worsley, KJ

Schyns, PG

Arguin, M

Gosselin, F

机构：

[1] Univ Montreal, Dept Psychol, Montreal, PQ H3C 3J7, Canada

[2] McGill Univ, Dept Math & Stat, Montreal, PQ, Canada

[3] Univ Glasgow, Dept Psychol, Glasgow, Lanark, Scotland

来源：

JOURNAL OF VISION | 2005年 / 5卷 / 09期

关键词：

classification images; reverse correlation; Bubbles; random field theory;

D O I：

10.1167/5.9.1

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

Despite an obvious demand for a variety of statistical tests adapted to classification images, few have been proposed. We argue that two statistical tests based on random field theory (RFT) satisfy this need for smooth classification images. We illustrate these tests on classification images representative of the literature from F. Gosselin and P. G. Schyns ( 2001) and from A. B. Sekuler, C. M. Gaspar, J. M. Gold, and P. J. Bennett ( 2004). The necessary computations are performed using the Stat4Ci Matlab toolbox.

引用

页码：659 / 667

页数：9

共 57 条

[41] Identification of the eye-brain-hand system with point processes: A new approach to simple reaction time [J].