Perceptual Coherence : Hearing and Seeing

102 Perceptual Coherence
Buracas and Albright (1999) created a measure of the efficiency in the
response by dividing the mutual information by the total information in the
response:
E = mutual information/total information. (3.12)
The authors estimated that roughly 50% of the total information from the
spike trains of the retinal ganglion cells reflects variation in luminance and
50% of the total information from the spike trains in the medial temporal
visual region reflects the direction of motion of random arrays (discussed
later). Borst and Theunissen (1999) also estimated that the efficiency is
about 50%, and that each additional spike reduces the uncertainty by 50%.
One continuing question surrounding information theory has been
whether the auditory and visual systems are matched to the statistical properties
of the sensory energy so that the encoding can be done in ways that minimize
redundancies (there is no need to waste sensory elements on a u after
encoding a q). The goal would be to avoid encoding information that is found
in other parts of the signal and thereby create an efficient low-redundancy
sensory code. Yet, efficiency may not be as critical as factors such as reliability,
the absolute need to avoid catastrophic mistakes (not hearing or seeing
the movements of predators), or the ability to encode completely novel and
unexpected objects. Moreover, some of the sensory information may not
have any perceptual consequence or may even disallow the creation of object
categories. In sum, information theory really constitutes a theory about perceptual
processing and provides a way of organizing experimental outcomes,
but we should be somewhat wary of assuming that sensory systems have developed
to maximize the rate of mutual information transmission.
Bayesian Theory: Converting Information and
Prior Probabilities Into Decisions
Perceiving is an ongoing process made in a probabilistic world and should not
be conceptualized as a series of independent one-shot decisions. The perceiver
must build up the conditional probabilities Pr(s � r) and Pr(r � s), linking
the neural response (i.e., the perceptual image) to the stimuli in the physical
world. Without the context and physical regularities in some way limiting the
open-ended set of alternatives, the perceiver would be overwhelmed by the
possibilities. Expectations are built up over time as the perceiver (1) learns
about the set of possible neural signals and images associated with any auditory
or visual object, (2) learns about the frequency of occurrence of the objects,
and (3) learns about the gains and losses associated with correct and
incorrect perceptual actions. Helmholtz (1867) characterized perception as
unconscious inference, estimating from past experience which physical stimulus
would most probably have generated the proximal excitation. Originally