Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

August 1, 2005, Vol. 17, No. 8, Pages 1700-1705
(doi: 10.1162/0899766054026666)
© 2005 Massachusetts Institute of Technology
Motion Contrast Classification Is a Linearly Nonseparable Problem
Article PDF (57.7 KB)
Abstract

Sensitivity to image motion contrast, that is, the relative motion between different parts of the visual field, is a common and computationally important property of many neurons in the visual pathways of vertebrates. Here we illustrate that, as a classification problem, motion contrast detection is linearly nonseparable. In order to do so, we prove a theorem stating a sufficient condition for linear nonseparability. We argue that nonlinear combinations of local measurements of velocity at different locations and times are needed in order to solve the motion contrast problem.