Similarity is one of the central problems of psychology. It underlies
object recognition and categorization, which are crucial to much of modern
cognitive research, not to mention survival in the real world. It
underlies transfer of learning, errors of memory, perceptual organization,
social bonding, and many other experimental problems one might choose almost
at random from the psychological literature. Distinguished thinkers
from Aristotle to modern psychologists such as Shepard (e.g. 1987),
Tversky (e.g. 1977), and Nosofsky (e.g. 1992) have wrestled with
it. It is no surprise that similarity plays a key role in the subject
matter of several of the other chapters in this book, such as in
discussions of object and pattern recognition (Cook,
2001, Kirkpatrick, 2001,
Chase & Heinemann, 2001), categorization
Young & Wasserman, 2001), and attention (P.
Blough, 2001, Shimp, Herbranson, &
Fremouw, 2001). What is similarity and how is it measured in birds? This chapter
is a brief review of some answers to this question, together with examples
from existing research.
Nature of Similarity
Similarity is a relationship that holds between two perceptual or conceptual
objects. The discussion here will be restricted to similarity considered
as the perceptual resemblance of objects to one another. Other chapters
in this book are concerned with more abstract relationships (e.g. Young
& Wasserman, 2001). Here, the term “object” will mean any reasonably
unitary stimulus, including real objects, such as a stone or a tree, but
also a patch of light on a screen, a moving dot, or a bird call.
Similarity as perceptual resemblance is a psychological construct in
somewhat the same way that such sensory attributes such as hue, brightness,
or pitch are constructs or intervening variables. Like such attributes,
similarity depends heavily on the physical characteristics of stimulus
objects, but this dependence is complex, and in the case of similarity
the details of the physical-psychological relationship are usually unknown.
Fortunately, similarities may be specified independently of any physical
measures of the stimuli involved; that is, one may determine the
similarities among a group of objects from behavioral responses to the
objects without specifying anything about them except which behavioral
measures go with which object (see multidimensional
scaling). However, as will be illustrated shortly, one
important use of similarity structures is to help to identify psychophysical
relations that are difficult to determine in other ways.
For animals similarity is derived from such measures
as discrimination errors, generalization response rates, transfer responses,
and discriminative reaction times, but similarity cannot be directly equated
with such measurements. For example, as will be illustrated below, a generalization
gradient does not define the similarity of test stimuli to a training stimulus,
though a gradient may contribute to such a definition. (See generalization
gradients in the measurement section.)
The reasons for taking the trouble to go beyond physical measures
of stimuli and raw behavioral response data to construct scales of similarity
are somewhat analogous to those for going beyond physical measures to construct
scales of psychological attributes. Measures of hue, brightness,
or pitch are used to construct stimuli and to state psychological results
because they enter into much simpler relations with behavior than do wavelength,
intensity, and frequency. They also provide generality, for after
they are determined in one task they may, if used with care,
help organize and predict the results of other tasks that share the same
stimuli. Likewise with similarity. The most striking example
of a broad generalization of this sort is Shepard’s Universal Law
of Generalization, which states that the probability of a response learned
to a stimulus S decays exponentially with dissimilarity between a test
stimulus and stimulus S (e.g. Shepard, 1987).
One reason for caution in applying similarity relations across situations
is that variables may affect the behavioral measures through which similarity
is determined without affecting similarity. For example, if pigeons
get food in the presence of one random set of photos and do not get food
in the presence of another set of photos, the birds may respond equally
to all the “food” items and withhold response to all the “no-food”
items. This presumably does not mean that pigeons find the photos
within each group perceptually similar to each other, and dissimilar to
those in the other group.
On the other hand, similarity between objects is not solely dependent
on the characteristics of those objects. It is also affected by other present
and immediately past stimuli, as well as long-term experience with related
objects. For humans, a notorious case in point is the effect
of experience on similarity among phonemes. A well-known example
is that native English speakers find spoken “L” and “R” quite distinct,
whereas to native speakers of Japanese they sound extremely similar.
Because one of the advantages of work with non-human animals is the possibility
of controlling past experience with stimuli, an interesting and challenging
task is the study the conditions under which such “perceptual learning”
occurs, and in separating such perceptual learning from of other sorts
Until recently, students of animal behavior have often been casual in
their assumptions about stimulus properties, including similarity.
Typically, stimuli were implicitly assumed to have certain similarity
relations, which might mean that similarity is assumed to be inherent in the
stimulus objects (red keys are “physically” similar to orange keys) or
it might mean that similarity depends on how the stimuli look to the experimenter
(red is similar to orange because it looks that way to me).
The first assumption ignores the findings of psychophysics. The second
is anthropocentric (or, more exactly perhaps, solopsistic), and easily
examples: similar (to us) white flowers may look quite different
to bees because of their differing reflection of ultraviolet light.
Of course, individual humans differ in sensory capacity (e.g. - colorblind
vs. normal, see Figure 1), but more interestingly their perception is affected by training
(a trained musician hears things inaudible to an untrained person, or in
the phoneme example cited above).
The remainder of this chapter consists mainly of two parts having to
do first with some conceptual and theoretical issues surrounding similarity,
and second with the measurement of similarity in birds.
Next Section: Theoretical