Behavioral Ecology Vol. 11 No. 5: 502-506
© 2000 International Society for Behavioral Ecology
The cost of limited attention in blue jays
Nebraska Behavioral Biology Group, School of Biological Sciences, University of Nebraska, Lincoln, NE 68588-0118, USA
Address correspondence to R. Dukas at the Department of Biological Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. E-mail: rdukas{at}sfu.ca .
Received 1 September 1999; revised 28 December 1999; accepted 6 January 2000.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSDISCUSSIONREFERENCES |
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Experiments with fish and birds suggest that animals are unable to simultaneously allocate sufficient attention to tasks such as the detection of an approaching predator while searching for cryptic prey. We quantified the effects of limited attention on performance in controlled laboratory settings and report here the first direct evidence that attending to a difficult central task simulating foraging deters a bird's ability to detect a peripheral target, which could be a predator. Our results fill a gap between ecological and neurobiological studies by illustrating that, although attention is an efficient filtering mechanism, limited attention may be a major cause of mortality in nature.
Key words: attention, blue jays, Cyanocitta cristata, survival, vigilance.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSDISCUSSIONREFERENCES |
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Neurobiological research on humans and monkeys indicates that attentional mechanisms direct the brain's limited computational resources to the most relevant information, filtering out less important information. Consequently, subjects that pay more attention to a central difficult task compensate by devoting less attention to a secondary task (Desimone, 1998
;
Desimone and Duncan, 1995;
Hillyard et al., 1998;
Kastner et al., 1998). For
example, Rees et al. (1997)
instructed human subjects to focus on a linguistic task appearing at the
center of a computer display, which also included moving stimuli at its
periphery. Behavioral measures and brain imaging revealed that the subjects
devoted less attention to the moving stimuli when the linguistic task was
difficult (detecting bisyllabic words) than easy (detecting uppercase
letters). If the mechanisms of attention studied in humans and monkeys are
shared by other species, the issue of limited attention is of critical
relevance for ubiquitous behaviors such as diet choice and balancing tasks
that must be carried out simultaneously, such as food search and predator
avoidance (Dukas, 1998b;
Dukas and Ellner, 1993;
Milinski, 1990).
A number of studies are consistent with the hypothesis that limited
attention constrains forager performance. Some of these studies documented a
change in foraging behavior after exposure to model predators
(Metcalfe et al., 1987;
Milinski and Heller, 1978).
Such change could be caused by reduced attention to food when more attention
was devoted to predator avoidance. For example, Milinski
(1984) reported that after
exposure to a model of an avian predator, three-spined sticklebacks preferred
to forage at daphnia swarms of lower density, and that such swarms allowed
them higher detection rates of approaching predators. Indeed, Godin et al.
(1988) documented higher
mortality rates of fish hunting for daphnia at higher densities. Alternatives
to limited attention, however, such as fear-induced physiological changes
(Lima, 1998), or reduced
visibility at higher food density, may also account for the above results.
Another category of studies consists of reports that animals engaged in
feeding, playing, or fighting are either less likely to respond to an
approaching predator or respond to the predator at a shorter distance than
when not engaged in other activity
(Blumstein, 1998;
Brick, 1998;
Krause and Godin, 1996). A
likely alternative in these cases is a lower motivation to immediately respond
to the predator (Ydenberg and Dill,
1986). All these studies, however, are highly suggestive and
invite a more controlled set of experiments.
Consider a blue jay perching on a tree trunk and directing its gaze toward
the bark in search for cryptic insects
(Endler, 1984;
Sargent, 1976). The blue jay
has the visual ability to simultaneously detect approaching predators while
foraging (Fite and Rosenfield-Wessels,
1975; Martin,
1986), but such detection may be hindered due to limited
attention, at least when the foraging task is difficult and
attention-demanding. We simulated such a foraging scenario under controlled
laboratory conditions to quantify the importance of limited attention.
Specifically, we predicted that jays would have a higher probability of
detecting peripheral targets when engaged in an easy than in a difficult
central search task.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSDISCUSSIONREFERENCES |
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Subjects
The five blue jays (Cyanocitta cristata) used in the experiment were captured as nestlings in Lincoln, Nebraska, USA, approximately 1 year before the experiment and were hand raised in the laboratory. During the experiment, the jays were maintained at 80% of their ad libitum body weight with controlled daily feedings of turkey starter and Lefeber brand food pellets. The jays were housed in individual cages, with water available, at a constant room temperature of 27°C and on a 14 h:10 h light:dark cycle. Before the experiments, we trained the jays to peck at targets presented on a computer monitor. By the end of the training period jays were familiar with the experimental protocol and stabilized in their performance.
Apparatus
We trained and tested the jays in an operant chamber (approximately 50
x 50 x 50 cm) with opaque walls located in a small, darkened room.
A white noise generator was played throughout the experiment to mask outside
sounds. Stimuli were presented on a computer monitor embedded in the front
wall of the chamber. A house light mounted above the monitor provided dim
light throughout the experiment. We attached a clear Plexiglas sheet to the
front of the monitor by springs to prevent damage to the monitor and to the
jays' beaks. An infrared touch screen reported the location of each peck
directed at the screen. A wooden perch was positioned approximately 10 cm from
the touch screen and 15 cm above the chamber floor. Jays standing on the perch
could readily peck at targets presented on the monitor screen and reach the
food rewards. The rewards were half pieces of mealworms (Tenebrio
molitor), which were delivered via a Davis UF-100 universal feeder into a
food cup mounted to the left of the lower left corner of the monitor. At the
moment of reward delivery, a light above the food cup was turned on and fully
illuminated the food cup for 3 s. All stimulus presentations, schedules of
reward delivery, and data recording were controlled by a personal computer
programmed in Borland C.
Experiment 1: central task difficulty
Protocol
Our goal was to create two levels of central task difficulty. We wanted to
achieve this goal by presenting a target among either a small or large number
of nontarget background items, which were isolated pieces of the target,
placed at randomly chosen locations on every trial
(Figure 1d). In experiment 1 we
tested whether we could indeed alter the difficulty of the search task by
changing the number of these distractors included in the displays. In this
preliminary experiment, the display consisted of a red central circle, a
monochromatic target, the central target (a caterpillar 15 pixels long and 5
pixels wide) shown at a random location within the central circle, and a known
number of background items (Figure
1; see below). The target caterpillar appeared inside the circle
in randomly determined 50% of the trials (positive trials), with the remaining
trials being negative. Display duration was varied randomly between 50 to 500
ms, with each duration presented 10 times in a 100-trial daily session. There
were 3 types of daily sessions, in which the central circle contained 1, 5, or
10 background items. The jays were trained to peck at the target during
positive trials and to avoid pecking during negative trials. The experiment
was conducted with three jays, each jay performing four blocks, with each
session type presented once in random order within a 3-day block.
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Results
A larger number of background items was associated with a lower frequency
of correct responses. The percentages of correct responses were 81.00 ±
2.50, 67.00 ± 3.20, and 56.50 ± 1.75 with 1, 5, and 10
background items, respectively (repeated-measures ANOVA on arcsine-transformed
proportions, F2,4 = 30.7, p <.005). The
results of this experiment indicated that we could indeed alter the central
task difficulty by modifying the number of background items in the central
circle.
Experiment 2: the cost of limited attention
Protocol
Each daily session consisted of 50 trials. A jay initiated each trial by
pecking a red circle at the center of the monitor
(Figure 1). After a brief
delay, a display was presented for 500 ms. All displays consisted of a red
central circle, two red peripheral ellipses, and a monochromatic target,
either a central target (a caterpillar 15 pixels long and 5 pixels wide) shown
at a random location within the central circle with probability 0.5, or a
peripheral target (a moth 20 pixels in maximum length and 17 pixels in maximum
width) shown at a random location inside the left or right ellipse with
probability 0.25 for each side (Figure
1). We did not use simulated predators because these can have
uncontrolled behavioral effects unrelated to attention, such as fear or
reduced motivation to feed (Lima,
1998), which we wished to eliminate. Direct observations of the
jays confirmed that they faced the center of the screen during display
presentations and that they did not move their heads from one side of the
monitor to the other during the brief display presentations.
During the experiment, the circle and two ellipses always contained
nontarget background items, which were isolated pieces of the targets, placed
at randomly chosen locations on every trial
(Figure 1d). The number of
background items inside the central circle was small during center easy
sessions and large during center difficult sessions. The number of background
items inside the peripheral ellipses was small and constant across all
sessions (Figure 1d). After the
brief presentation of the display, the target and background items were
cleared, but the three red circles remained for additional 1000 ms
(Figure 1e). Thus, a jay had a
total of 1500 ms to peck at the monitor. A single peck terminated the trial. A
peck directed at the circle or ellipse containing the target ("correct
detection") was rewarded with half a mealworm. A peck at a wrong circle
or ellipse resulted in three beeps followed by a delay of 1 min. Jays
attempted to avoid such delays, which served as mild punishment
(Kamil et al., 1993). If a jay
did not peck at all, the next trial followed after 5 s delay. The experiment
consisted of 12 2-day blocks, each containing the 2 session types in random
order. Five jays were used.
We predicted that during center easy sessions, jays would use a broad focus of attention toward much of the monitor, and during center difficult sessions, they would direct a narrow focus of attention toward the central circle because the central circle was the location most likely to contain a target. Thus we predicted that the frequency of peripheral target detection would be lower in the center difficult than center easy sessions.
Results
The jays correctly detected 38% of the peripheral targets during the center
easy sessions but only 14% during the center difficult sessions
(repeated-measures ANOVA on arcsine-transformed proportions,
F1,4 = 112, p <.001;
Figure 2a). In contrast, the
frequency of correct detections of the central target was 81.7% during the
center easy condition, virtually identical to the 82.9% observed during center
difficult sessions (F1,4 = 0.02, p >.8;
Figure 2a), suggesting that by
allocating more attention to the central circle, jays were able to maintain a
high detection frequency of the central target.
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Incorrect detections consisted of wrong pecks, meaning that the jays pecked at a circle not containing the target, and no pecks, meaning that the jays did not peck at all during the brief display presentation. It is relevant to report the distribution of these distinct categories. Incorrect detections of peripheral targets consisted of 66% ± 1.9% wrong pecks and the rest no pecks during center easy sessions and 82% ± 1.6% wrong pecks and the rest no pecks during denter difficult sessions. Incorrect detections of central targets consisted of 65% ± 2.4% wrong pecks and the rest no pecks during center easy sessions and 57% ± 2% wrong pecks and the rest no pecks during center difficult sessions.
An alternative explanation for our results is that jays required a shorter search time for scanning the central circle and thus spent more time scanning the peripheral ellipses during the center easy than during center difficult sessions. This possibility is not supported by the latency data, as the time required for correct detection of a central target (measured from display onset) was similar during the center easy and center difficult sessions (F1,4 = 0.02, p >.8; Figure 2b). The latency for correct detection of a peripheral target was also similar under either session type (F1,4 = 0.07, p >.8; Figure 2b).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSDISCUSSIONREFERENCES |
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Our results demonstrate that limited attention constrains a forager's ability to notice peripheral targets, which could be approaching predators, when involved in challenging foraging tasks. These results suggest that in nature, foragers engaged in more difficult food-detection tasks may incur higher rates of predation. Alternatively, in habitats with higher predation risk, foragers may allocate more attention to predator detection and less attention to food search (see Dukas, 1998b
; Dukas and Ellner,
1993; Milinski,
1990). This may result in reduced food intake, and consequently,
lower fitness due to a decrease in growth rate and body condition
(Lima, 1998). Our findings are
consistent with previous experiments
(Godin and Smith, 1988;
Krause and Godin, 1996;
Lawrence, 1985;
Metcalfe et al., 1987;
Milinski, 1984;
Milinski and Heller, 1978),
all suggesting that foragers under challenging conditions could not devote
sufficient attention to the dual task of searching for food and detecting
predators. As we mentioned in the introductory section, these studies did not
consist of critical tests for the effect of limited attention. Our results are
also in agreement with studies in pigeons, where results have indicated that
selective attention affects subjects' food searching behavior (Blough,
1969,
1991; Langley,
1996; Riley and Leith,
1976). For example, Vreven and
Blough (1998) documented a
decrease in target detection accuracy by pigeons when the number of either
potential targets or nontargets increased. We have augmented previous studies
by critically evaluating the possible role of limited attention for the
ubiquitous task of finding food and detecting predators at the same time while
controlling for alternatives.
Our experiments are relevant for many species and foraging scenarios that
allow simultaneous search for food and predators. Examples include fish
foraging in open water and birds feeding on tree trunks or branches. Moreover,
our experiments are also relevant for the food search periods by animals such
as ground-feeding birds, which alternate between head-down postures used for
food search, and head-up positions used for scanning the environment for
predators. Although earlier studies assumed that such ground-feeding birds
cannot detect predators while in the head-down position, it is now established
that they can (Lima and Bednekoff,
1999). However, the ability to detect approaching predators while
focusing attention on food may be low, at least when the feeding task is
difficult.
We designed our experiment to critically test for the effect of limited
attention, while compromising on some aspects of natural foraging situations.
First, we used two target types rather than food and a predator. An image of a
predator or severe punishment could dramatically alter the jays' behavior,
which we wanted to avoid. One might argue that our results documenting reduced
ability to notice a peripheral target associated with reward under more
difficult central task conditions would not be replicated when the peripheral
target is associated with predation. There are two aspects to such possible
criticism. First, it is feasible that under demanding situations jays can
simply allocate more attention to handle dual tasks. This is probably possible
to some extent. However, the fact that all animals studied so far do not
usually possess larger attentional capacities suggests that there is some cost
associated with increasing the amount of information they process at the same
time. One possible cost is a higher rate of exhaustion under such demanding
information load (Dukas,
1998b; Dukas and Clark,
1995b). This idea requires empirical evaluation as outlined in
Dukas and Clark (1995b).
Another line of criticism is that jays would always allocate more attention
to the periphery if they anticipate predation rather than merely another
feeding opportunity. This is a likely scenario, but it would probably require
the jays to devote less attention to the central task. In general, jays and
other species would probably alter the optimal allocation of attention between
feeding and predator avoidance in response to short-term requirements and
information about predation risk, with the changes in allocation of attention
being correlated with changes in performance on the associated tasks. An
experiment by Metcalfe et al.
(1987) indicating that
juvenile salmon showed reduced ability to select optimal food items after
exposure to predators accords with the possibility that the fish devoted more
attention to predator avoidance and less attention to food after perceiving
the predator. As we mentioned in the Introduction, however, such an experiment
does not exclude the likely alternative of fear-induced physiological changes,
which diminish foraging performance.
Another somewhat unnatural aspect of our protocol is that we were concerned with static visual targets even though foragers are also sensitive to abrupt movement. Some animals also are highly responsive to other stimuli, such as smell or sound, to increase the probability of detecting approaching predators. Nevertheless, our approach is highly relevant for many natural situations because predators typically attempt to minimize detection by moving slowly, quietly, and against the wind. Moreover, predators may attempt to capture an animal while it focuses attention on food, as indicated by the animal's body posture and behavior. As we demonstrated here, when an animal focuses attention on food, even relatively salient stimuli may go unnoticed.
In line with the neurobiological research on attention, we have focused on
information that must be processed at the same time. Foragers can partially
mitigate the negative effect of limited attention by alternating between
periods in which most attention is devoted to food and intervals in which most
attention is directed toward scanning the environment for predators. Such
behavioral patterns have been addressed by studies on antipredator vigilance,
although these studies usually focus on species such as ground-feeding birds,
where feeding and predator vigilance periods can partially be identified by
the head-down and head-up positions respectively
(Lima and Bednekoff, 1999;
Lima and Dill, 1990;
Pulliam, 1973).
Elaborate research on attention has been conducted only on humans and
monkeys. Experiments using direct electrophysiological recordings or brain
imaging have unambiguously established that focusing more attention on a task
is associated with enhanced activity of the neurons processing information
related to that task and improved behavioral performance on the task. At the
same time, the processing of information associated with a secondary task is
suppressed, and, consequently, performance on the secondary task is reduced
(Desimone, 1998;
Desimone and Duncan, 1995;
Hillyard et al., 1998;
Kastner et al., 1998;
Rees et al., 1997). It is
clearly advantageous to filter out unimportant information and focus only on
the relevant, but attention cannot be perceived only as an efficient filtering
mechanism, because animals often encounter a larger amount of relevant
information than they can process at the same time. Under such conditions,
attentional mechanisms allow allocation of attention to what is perceived as
the most important tasks. Sometimes, however, animals may fail to attend to
peripheral information, which may be an approaching predator.
We have recently replicated our results indicating that limited attention
constrains foraging performance in another study using a distinct protocol
(Dukas and Kamil, manuscript in preparation). While our empirical results and
earlier formal theoretical research (Dukas and Clark,
1995a,b;
Dukas and Ellner, 1993) bring
the idea of constraints on information processing closer to behavioral
ecology, this issue is well established in the cognitive sciences
(Behrmann and Haimson, 1999;
Desimone and Duncan, 1995).
Still, integrating issues such as limited attention within behavioral ecology
invites the question, why is attention limited? We can confidently answer that
the limitation in question is not either within the sensory system or specific
to the visual modality. For example, at a cocktail party, we tend to focus our
attention on one conversation at a time, even though our ears can receive
sounds from numerous conversations.
Although many neurobiological studies (see
Behrmann and Haimson, 1999, for
the latest ones) have focused on the mechanisms of attention, the question of
what determines optimal attentional capacity has not been explicitly
addressed. At some superficial level, it is easy to accept the notion that
there must be a ceiling on the amount of information that can be processed at
any given time. Information processing requires enormous computation by
neurons; hence the number of neurons and limitations on the number of
interconnections among neurons must allow only for some finite amount of
information to be processed at the same time. Due to limited knowledge, we
cannot at this time go further than this general argument. More explicit
analyses of optimal cognitive abilities would require data not yet available
about the cost associated with cognitive ability and the physiological and
phylogenetic constraints involved (see Dukas,
1998b,
1999).
In sum, at any given time, the information received by sensory systems may
far exceed an animal's processing ability
(Desimone, 1998). As a result,
some relevant information must be left unprocessed, even if this results in
heightened risk of predation or inefficient foraging. In this context, the
functional significance of attentional mechanisms would be to filter out some
information, allowing focus on the information expected to have the greatest
effect on fitness (Dukas,
1998b; Dukas and Ellner,
1993). This is an example of how cognitive abilities can be
central to ecological concerns, and why ecological insight is relevant for
cognitive science. An important issue for future research at the interface of
cognition and ecology (Balda et al.,
1998; Dukas, 1998a,
1999;
Shettleworth, 1998) is
identifying the neurobiological, computational, and phylogenetic mechanisms
that have shaped limited attentional capacity.
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ACKNOWLEDGEMENTS |
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We thank A. Bond, C. Cink, N. Ternus, C. Smith, M. Belik, B. Gibson, and M. Sinsel for assistance and comments on the manuscript, L. Bernays, K. Cheng, and D. Westneat for comments, and the National Institutes of Health for financial support.
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