116 Foundations of Visual Perception
obtained in the one-parameter Bayesian local grouping func-
tion (r=.89).
In the conclusion of this section, we wish to emphasize the
profound theoretical repercussions of the kind of analysis un-
dertaken by Geisler et al. (2001). These authors looked for a
foundation of the principles of perceptual organization in
the statistics of the natural world and discovered a covaria-
tional structure in these statistics. Furthermore, Geisler et al.
showed that under minimal assumptions, the regularities of
environment can predict human performance in simple per-
ceptual tasks. The findings of Geisler et al. imply that optical
stimulation does contain information for perception, in con-
trast to the view held by the Gestaltists. The information is
available for perceptual systems to develop the correspond-
ing sensitivities and to match the perceptual capacities of the
organism to the structure of the environment.
As Geisler et al. (2001) pointed out, the rapidly growing re-
search in neural networks shows that self-organizing networks
(such as in Kohonen, 1997) are sensitive to the covariational
structure of their inputs. This suggests that self-organizing
neural networks could provide a useful tool in guiding our
search for the match between the perceptual capacities of
the biological organisms and the statistical structure of their
environments.
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