Perceptual Coherence : Hearing and Seeing

142 Perceptual Coherence
frequency and spatial orientation or by frequency and time. For both there
are trade-offs between the frequency resolution and the time or orientation
resolution.
Experimental Physiological and Perceptual Outcomes
Using Natural Stimuli
Even though the environment may be made up of many processes that can
be modeled in terms of 1/f c power laws and models of cortical cells display
a sparse firing distribution, that does not mean that (1) the neural cells actually
are organized to yield sparse coding, and (2) people are sensitive to
the self-similarity of the processes. Moreover, although it may be true that
people can distinguish between auditory and visual fractal representations
based on different values of the frequency exponent, that still does not necessarily
imply that people perceive the fractal structure itself.
Experimental Physiological Outcomes
Vinje and Gallant (2000, 2002) created a sequence of visual images that simulated
what a monkey would see if it scanned a static natural scene and
recorded from neurons located in area V1 of two awake macaque monkeys.
Vinje and Gallant were particularly interested in how the firing of a classical
receptive area is influenced by stimulation of the surrounding area (the nonclassical
receptive field described in chapter 2). The theoretical and computation
approaches described above hypothesize that area V1 uses a sparse code
to efficiently represent natural scenes (remember, natural scenes have a great
deal of built-in redundancy, so that sparse codes would be effective). Vinje
and Gallant hypothesized that stimulation of the nonclassical response field
increased the degree of sparseness. The results demonstrated that indeed a
sparse code best represented the firing patterns found in the roughly 60 neurons.
Moreover, as the nonclassical receptive field increased in size, the
sparseness of the firing increased due to the nonlinear receptive field interactions
(compare figure 3.15C to figure 3.15B). Individual neurons became
more selective in responding to complex stimuli, so that the kurtosis of the
firing distribution increased. Stimulation of the nonclassical receptive fields
reduces the response to noise more than it reduces the firing to stimulus properties,
and that increases the efficiency of the coding. Vinje and Gallant found
that the degree of sparseness was the same for sequences of black-and-white
gratings and natural movies, suggesting that it is the correlated energy at different
orientations in both types of images that created the sparse coding.
Perez-Orive et al. (2002) presented a particularly compelling example of
sparse coding in the olfactory system of locusts. Roughly 90,000 receptor
neurons converge on about 1,000 excitatory projection neurons in the ol-