Call for Papers: Special Issue

Finding visual features:
Using stochastic stimuli to discover internal representations

In recent years psychophysicists have developed techniques for correlating noisy stimuli with behavioral decisions (‘classification images’) while neuroscientists have developed related techniques for correlating noisy stimuli with neural responses (‘reverse correlation’), both in an effort to infer the internal features that mediate perception. At the same time, cognitive scientists have been testing mathematical models of how observers make categorical decisions about noisy stimuli. And in parallel, computer scientists, mathematicians, and statisticians have been developing efficient algorithms and optimal methods for classifying noisy targets into categories defined by humans, and for identifying the stimulus properties that evoke neural responses. In December, 2004, a Neural Information Processing Society (NIPS) workshop brought together researchers from these fields to share and discuss these diverse approaches to solving their common problem of feature induction.

This special issue of the Journal of Vision is designed to allow full expression of these ideas, and to encourage additional work in this area. We invite articles on the general theme of induction of internal features from noisy response data. We emphasize that contributors are not restricted to participants at the NIPS 2004 workshop. We encourage submission of original research, reviews, and theoretical commentaries.

Appropriate topics include, but are not limited to:

• Higher-order and non-linear classification image techniques
• Neural reverse correlation techniques to extract higher-order kernels
• Computational algorithms to infer features from noisy classification data
• Methods for using fine-grained behavioral measures (e.g., confidence ratings, reaction times) to improve feature inference.

Guest Editors:

Jason M. Gold
Indiana University, Bloomington, IN
jgold@indiana.edu

Richard Shiffrin
Indiana University, Bloomington, IN
shiffrin@indiana.edu

James Elder
York University, Toronto, Canada
jelder@yorku.ca

Jack Gallant
University of California, Berkeley, CA
gallant@socrates.berkeley.edu

Deadline for submissions:

Target publication date: