To shift attention from one searching image to another, birds often rely on contextual
stimuli to figure out what to search for next. Multiple established templates may be stored
in long-term memory, waiting for some linked stimulus to call one of them up and make
it the center of attention. In lab experiments, human subjects remember the visual features
of the most recently detected target and use them as the template for a searching image.
It is called repetition priming. (Kristjánsson & Campana, 2010). Priming of
attention by the last detected target is similarly common in avian visual search
(Pietrewicz & Kamil 1979,
Blough 1989, 1991,
Langley et al. 1996,
Bond & Kamil 1998,
Bond & Kamil 1999), where it
is most apparent when targets are difficult to detect, diverse in appearance, and
displayed on complex, textured backgrounds
(Bond & Kamil 2002,
Bond & Kamil 2006,
But searching images can also be activated by an associative cue, an otherwise
arbitrary stimulus that is correlated with the occurrence of the target. The cue does not
need to have a physical resemblance to the sought-for item. For James Bond, even just the
verbal description of his target fish could suffice to deploy a searching image (Fleming 1960).
Cuing has long been the primary method for manipulating attention in human visual search
studies. Instructing a subject to watch for a green “T” in the next display, for example,
cues her attentional focus to a particular combination of shape and color and causes
distracting alternatives to be ignored. This process depends on semantic memory for the
association between the cuing stimulus (i.e., the words “green T”) and the visual features
of the target (Wolfe 1998, Chun 2000).
Associative cuing also seems to play a role in birds, especially
when their previous searching image has faded due to lack of reinforcement. There
is observational evidence suggesting that birds use previous successful foraging
at a given location or the color or texture of the substrate to determine what type of prey
should be sought (Heinrich & Collins 1983, Krebs et al. 1974, Getty & Pulliam 1991, 1993).
One of the best examples is from Croze's (1970) field study of foraging in wild carrion crows.
Croze scattered red-painted mussel shells, each covering a small piece of meat, on natural
areas of ocean beach. The local crows rapidly learned to search for them and flip them over.
When the crows were subsequently offered painted red shells of other kinds -- like razor clams
or cockles -- the birds investigated them in areas where they had previously found rewarding
red mussels. But in other locations, novel red shells were often overlooked, suggesting that
features of the familiar foraging site may have specifically cued a search for red targets.
The inference is tempting, but any account of a cognitive mechanism requires careful
experimental designs to exclude alternative explanations, and associative cuing has been
hard to demonstrate under fully controlled conditions (Blough 1989,
The strongest form of the visual template hypothesis assumes that essentially the
same cognitive representation can be elicited by any sufficiently predictive
stimulus (Langley 1996, Bravo & Farid 2009, 2012), ranging from the location of
previous foraging successes, to the shape of a tree leaf, to the appearance of a prey
item that had just been found and eaten. So a foraging bird that noticed insect damage
on the new leaves of an oak tree might activate the same searching image as another
bird that had just finished feeding on an oak-leaf caterpillar. There is, however, a strong
distinction between repetition priming and associative cuing. Cuing is produced not by
the appearance of the target itself, but by stimuli that are secondarily reinforced by
having been associated with a prior prey detection. If a bird has found a caterpillar on a
leaf of a particular shape, it may later recognize the same shape on a different leaf and use the
association as a cue to a focused attentional search. The effect of secondary reinforcement,
however, fades rapidly the longer the time delay between a currently perceived stimulus
and the last relevant prey capture. Priming, in contrast, is the immediate consequence of
detecting and eating a prey item and is based on stimulus features that are intrinsic to
the prey. This close proximity between the prey stimulus and the food reward in priming
should have a stronger, longer-lasting effect than associative cuing. Given the diversity
of influences that can determine which template is chosen, it is essential to consider
whether cuing and priming operate in the same fashion -- whether they really do elicit
exactly the same searching image -- and whether it is possible for them to interfere with
Cuing and Priming Experiment
To test for the effectiveness of cuing versus priming and to look for interaction
effects when both are present, we trained blue jays to search for digital moths
(about the size of a housefly) on a computer touchscreen
(Goto, Bond, Burks & Kamil 2014).
Because the individual birds varied widely in how well they could detect these targets,
we needed to be able to adjust the task difficulty for each jay to insure equivalent
performance. We adopted Blough’s (1989, 1991) discrimination design, which presents targets
and comparable distractors on a visually flat background against which all stimuli are
clearly visible. Our targets were maximally distinctive from one another,
while maintaining a sufficient resemblance to the distractors to make discrimination
During initial training, each bird was taught a specific set of four rewarded targets.
In each detection trial, one of these targets was displayed among a varying set of
similar distractors. The figure above shows a sample display with a target (circled
here in yellow) and eleven distractors in the side panels. The central panel served as
a cue strip that provided information about what target to expect in the trial.
In this illustration, the cue strip is shown in black with diagonal lines, which is
equally associated with two of the four targets. It is, thus, an ambiguous cue
that does not specify which of the two targets to look for. Informative cue strips
that predicted a single specific target type were either in red with vertical lines
or green with horizontal lines. The cue strip was displayed just before the stimulus
array was shown and turned off during the actual search, thereby maintaining the
characteristic time relationship: associative cues in nature generally precede the
initiation of a search. We elicited repetition priming by presenting uniform blocks
of trials with an ambiguous cue, but a single target type,
and we contrasted those results with trials in which targets were presented in randomized
order. Test sessions included trials with stimuli that were 1) either correctly or
incorrectly cued; 2) either primed or unprimed; 3) both cued and primed; or 4) neither
cued nor primed. To control for effects from prior training, the study was divided into
two successive phases -- one with and one without repetition priming. Combining all sessions within
subjects across both study phases yielded a full experimental design, enabling us to
evaluate the relative effects of priming and cuing and to determine the nature of their
interaction in combined treatments.
Initial training was accelerated by priming -- the birds learned much more rapidly in
treatment sessions where the same target was repeated in successive trials. Learning was
significantly slowed when targets were both cued and primed, however, suggesting that the two
processes interfered with each other during training. When the birds were fully trained,
attentional effects showed up mainly when the target was not the focus of the current
searching template: Response time was higher in miscued trials during cuing sessions,
and accuracy was lower on primed trials following an unexpected target switch. A
combination of both cuing and priming greatly interfered with detection in unexpected trials,
apparently a result of the limited capacity of working memory, which insures that only one
searching image can be deployed at a time.
During initial training, the birds learned the characteristic features of all
four of their target types. Two targets were uniquely associated with particular colored
cues; the other two were both associated with the same noncolored cue. At the
start of each trial, therefore, the bird probably had available in long-term memory a
representation of each of the possible targets. The issue is how these
representations interacted in generating the searching image. Unlike human subjects in
laboratory studies, animals have to learn the significance of the cue from repeated
successful discoveries, so associative cuing in a natural environment can readily be
disrupted by variation in the abundance and appearance of the different target types.
The evidence in our experiment of interference between cuing and priming during both
training and testing makes it seem unlikely that these two processes can ever
simultaneously contribute to a real-world visual search in animals.
Cuing may only work well when the food items are not that difficult to see and are reliably
detected when present. It would also help if the target stimuli were distinctive from one
another and limited in
diversity. And of course, the cues themselves would need to be highly predictive
of eventual reward. Coincidentally, these are precisely the conditions in which repetition
priming is least useful and least likely to show a significant effect
Bond & Kamil 1999).
Situations in which both forms of attentional guidance operate at the same time
are, therefore, unlikely to be common in nature. What seems more probable is a sequence of
actions in which cuing or priming operate at different stages of the same search. So
cues from the location of a tree or the appearance of its leaves might attract a foraging
bird and direct its attention to particular branches. If the prey items are cryptically
colored, repetition priming would then become paramount, enhancing the success of subsequent
detections. Visual search is an inherently hierarchical activity (Curio, 1976), and there
is reason to expect different kinds of attentional guidance to dominate at different
points in the process.
Additional discussion of this issue can be found in our review article
(Kamil & Bond 2006),
and the whole concept of visual search in animals is placed in a broader context
in our book,
Concealing Coloration in Animals,
published in 2013 by Harvard U. Press.
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