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First published online March 28, 2008
Journal of Experimental Biology 211, 1180-1186 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.016683
Honeybees can recognise images of complex natural scenes for use as potential landmarks
1 Centre for Brain and Behaviour, Department of Physiology, Monash University,
Clayton 3800, VI, Australia
2 Institut fur Zoologie III (Neurobologie) Johannes Gutenburg Universität,
Mainz 55099, Germany
* Author for correspondence (e-mail: adrian.dyer{at}med.monash.edu.au)
Accepted 6 February 2008
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Summary |
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Key words: spatial vision, landmark, differential conditioning, foraging, navigation
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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; Giurfa et al.,
2001; Si et al.,
2003; Vladusich et al.,
2005; Zhang and Srinivasan,
2004). On a foraging flight in nature, a bee may fly several
kilometres to visit a rewarding patch of flowers
(Frisch, 1967), and honeybees
typically forage from flowers in both simple (open fields) and complex
(forests) environments (Steffan-Dewenter
and Kuhn, 2003). On each foraging trip bees may visit several
different locations (Menzel et al.,
1996; Reinhard et al.,
2004), and return several times after contributing the collected
food to the colony (Collett,
1992; Frisch,
1967). To efficiently conduct these flights, bees employ a variety
of sensory cues that include visual odometry, where the insect estimates the
distance travelled by the flow of spatial information sensed by the visual
system (Srinivasan et al.,
2000; Srinivasan et al.,
1997; Vladusich et al.,
2005), and/or the use of landmarks
(Chittka et al., 1995a;
Chittka et al., 1995b;
Collett and Zeil, 1997;
Vladusich et al., 2005).
Indeed, vision is a major modality in bee decision making for locating
reliable food sources (Chittka and Tautz,
2003; Srinivasan et al.,
2000; Vladusich et al.,
2005), but currently the capability of bees to use their spatial
vision to identify landmark cues is not well understood.
Previous work has demonstrated that bees use interactions between different
visual cues to navigate. For example, honeybees searching for a feeder in a
tunnel are more accurate when both odometric and landmark cues could be used
in combination (Vladusich et al.,
2005). If these cues are set in conflict then bees mainly rely on
landmark cues for searching (Vladusich et
al., 2005). However, if no odometric cues are present, the
reliability with which landmarks might be used is decreased
(Vladusich et al., 2005).
These findings fit well with the suggestion that the use of odometry by bees
might serve as a context setting cue to help distinguish landmarks that appear
similar (Collett and Collett,
2002). In complex foraging environments like forests, potential
landmarks including trees might be so numerous that the discrimination between
perceptually similar shapes is problematic for the limited visual acuity of
bees; potentially creating a dilemma that bees might not be able to `see the
trees for the wood' when searching for salient landmarks in a visually rich
environment. Currently, it remains unclear to what extent bees can use spatial
vision to discriminate between similar scenes, or recognise a `landmark' scene
from a perceptually similar scene whilst flying to rewarding flowers
(Collett and Collett, 2002;
Vladusich et al., 2005).
Although it has previously been suspected that honeybees have relatively
simple spatial visual capabilities for identifying landmarks (Horridge, 2005),
recent studies of the spatial discrimination capabilities of honeybees suggest
that, when provided with differential conditioning, fine spatial
discriminations can be made (Giurfa et
al., 1999; Stach et al.,
2004; Stach and Giurfa,
2005). For example, bees can learn to discriminate between complex
novel stimuli consisting of human faces, taken from a standard psychophysics
test (Dyer et al., 2005).
Furthermore, differential conditioning has revealed that bees can categorise
perceptually similar stimuli (for example, landscapes versus
non-landscape images) (Bernard et al.,
2007; Zhang et al.,
2004). Thus, there exists the possibility that despite having
relatively poor spatial acuity compared with vertebrate vision
(Land, 1997a;
Land, 1997b), bees may be able
to use their spatial vision to reliably identify and remember viewpoints of
complex scenes experienced during normal navigation to and from the hive. If
bees can learn to discriminate between such complex natural scenes this would
permit individuals to `self select' landmarks that are useful for navigation,
rather than have to rely only on infrequent salient landmarks.
Investigations where bees have received extended amounts of training to
perceptually similar visual stimuli suggest that they make complex decisions
about which stimulus to choose at a particular moment in time
(Chittka et al., 2003;
Dyer and Chittka, 2004a). For
example, bumblebees trained to perceptually similar colours allocate more time
to making decisions to improve accuracy, often choosing to abort an approach
to a stimulus and reject it (Chittka et
al., 2003). This is consistent with observations that during fine
spatial discrimination tasks bees may learn to examine and reject a
non-rewarded stimulus, in addition to learning the correct target stimulus
(Giurfa et al., 1999).
Importantly, if bees receive a punishment for visits to a distractor stimulus
(bitter tasting quinine hemisulphate) they elect to improve accuracy at the
cost of longer response times (Chittka et
al., 2003), although the physiological mechanisms underlying this
behavioural are not yet fully understood
(de Brito Sanchez et al.,
2005). When this type of complex decision making is observed in
human behaviour it is useful to mathematically model the data using signal
detection theory (Collishaw and Hole,
2000; Green and Swets,
1966). There is good evidence that modelling sophisticated
decision making with signal detection theory is relevant to explaining
behaviour in other animals including monkeys
(Thompson and Schall, 2000),
pigeons (Blough, 1967;
Sole et al., 2003) and mice
(Steckler, 2001). One recent
study has shown signal detection theory to be applicable for modelling
bumblebee behaviour (Lynn et al.,
2005).
In this study, we used a differential conditioning procedure
(Dyer and Chittka, 2004a;
Dyer and Chittka, 2004b;
Dyer et al., 2005;
Giurfa, 2004;
Giurfa et al., 1999;
Stach et al., 2004;
Stach and Giurfa, 2005) to
test if honeybees can visually discriminate and subsequently recognise the
types of visual scenes that might be encountered as potential landmarks if
flying through a complex forest-like environment. To analyse the behavioural
data, we used signal detection theory to model information on decisions made
by individual bees (Green and Swets,
1966; Lynn et al.,
2005; Marston,
1996).
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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), and then
trained to visit an experimental site 5 m away where 25% sucrose solution was
available for correct landings on a target stimulus. The bees were trained to
visit stimuli on a 50 cm rotating screen display where two target and two
distractor stimuli could be presented vertically on freely rotating hangers
with a landing platform (Dyer et al.,
2005; Horridge, 2005). This display presents stimuli at a number
of spatially random positions, and it is possible to change stimuli and
re-randomise arrangements during training. The advantage of the rotating
display is that it permits a bee to view stimuli at an unconstrained visual
angle, which may be important for bees potentially choosing to use either
configural and/or feature extraction strategies for learning stimuli
(Dyer et al., 2005;
Efler and Ronacher, 2000).
Stimuli were 6x8 cm achromatic photographs of trees with a variety of
branches, forming a complex visual scene like those a bee might encounter en
route in a foraging trip (Fig.
1). The scenes were chosen to be perceptually very similar by
including the only available low spatial frequency information in the lower
left hand side of each image so as to avoid the possibility of bees using
symmetry perception (Giurfa et al.,
1996) or topological differences
(Chen et al., 2003) in stimuli
to solve the task. The brightness for each image was determined in 8-bit
achromatic space using ImageJ software [NIH, Bethesda, MD, USA; 1A
117±63 (mean ± s.d.); 1B 116±5; 1C 113±58)], and
mean luminance for respective images was measure in the experimental
conditions with a Gossen Lunasix F exposure meter (Postfach, Germany) 15 cm
from the stimuli (1A 316 cd m–2; 1B 316 cd
m–2; 1C 316 cd m–2); thus the overall
intensity of the signals provided by each of the stimuli was practically
identical. Fast Fourier transform (FFT)
(Zhang et al., 2004) (ImageJ
software) confirmed that the stimulus images
(Fig. 1A–F) were highly
similar with respect to spatial frequency, compared to angular high contrast
geometric shapes like a diamond, square wave grating or a figure `Y'
(Fig. 1J–O). Previous
studies have demonstrated that bees provided with absolute conditioning
generalise between these high contrast shapes
(Gould and Gould, 1988;
Horridge, 2005).
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Finally, we found that if honeybees were only provided with absolute
conditioning to a target stimulus (e.g.
Fig. 1A) they failed to
discriminate this stimulus from the distractors, showing these were indeed
perceptually similar scenes for bee vision. To visually represent how these
stimuli might appear to the visual system of a bee
(Chittka and Geiger, 1995b)
Adobe Photoshop (Adobe Systems Inc., San Jose, CA, USA) was used to apply a 30
pixel Gaussian blur filter to each 236 pixel cm–1 image. This
application of a Gaussian filter has the effect of making a 0.3 cycles
deg.–1 square wave grating (0.67 contrast) indistinguishable
for a human viewer at a viewing distance of 57 cm, which approximately equates
to reducing the visual resolution of each scene to available data for the
limit of visual acuity of 0.3 cycles deg.–1 for honeybees
(Srinivasan and Lehrer, 1988).
Although the optical systems of bees and humans operate on different
principles of resolving spatial information
(Dyer and Williams, 2005;
Land, 1997a;
Land, 1997b), this technique
allows a reasonable representation of how the stimuli might appear to a visual
system limited to a visual acuity of approximately 0.3 cycles
deg.–1 (Fig.
1G–I).
Experiment 1
During training, each individual bee (N=10) was first provided
with absolute conditioning to target stimuli
(Fig. 1A) for at least 15
visits. Each time a bee landed it was able to collect a 10 µl drop of 25%
sucrose, and a second drop was also made available on a PlexiglasTM spoon
presented next to the landing stage. When the bee climbed onto the spoon it
was moved 1 m away from the screen so that stimuli could be exchanged and
rotated (Dyer et al., 2005).
Once a bee had learnt to fly to the apparatus correctly it was given
differential conditioning to the target stimulus, and a similar distractor
stimulus (Fig. 1B), which
contained 0.012% quinine (Chittka et al.,
2003). The punishment leads to motivation to perform a task to a
high level of accuracy (Chittka et al.,
2003). It was important that the bee first received some absolute
conditioning before training with quinine on the distractor stimulus,
otherwise a bee could encounter quinine before becoming highly motivated and
leave the test site. When a bee became satiated it returned to the hive and
all the test equipment was cleaned with 20% ethanol.
After each bee had made 120 responses to stimuli it was given a non-rewarded test with fresh stimuli where the first 20 landings on stimuli were counted to exclude any possible use of olfactory cues. After this non-rewarded test, bees were provided with reinforcement training for 10 visits to ensure motivation, and then given a non-rewarded transfer test that included the target stimulus and a novel stimulus (Fig. 1C). The two phases were thus used to separately evaluate both bee discrimination of learnt stimuli (which is a precondition to being able to recognise the target stimulus) and then bee ability to recognise a learnt stimulus from a novel distractor.
Experiment 2
Experiment 2 tested an additional group of bees (N=10) to evaluate
if bees can discriminate between the stimuli shown in
Fig. 1B and C. Following
differential conditioning to Fig.
1B as a target and Fig.
1C as a distractor, the bees were then given an additional
non-rewarded transfer test to evaluate if these bees could recognise the
stimulus in Fig. 1B from a
novel stimulus in Fig. 1A.
Experiment 2 thus controlled for the possibility of any discrimination in
experiment 1 being solely on the basis of an innate preference for stimulus in
Fig. 1A.
Experiment 3
Experiment 3 tested if honeybees could potentially learn complex natural
stimuli in a shorter period of training than was provided in experiment 1 or
2, and to evaluate if bees might be able to learn the task in a context where
the distractor stimulus did not contain any bitter solution. Experiment 3
tested an additional group of bees (N=10) to evaluate if bees can
discriminate between the stimuli in Fig. 1B
and 1C even if differential conditioning is for only 40 responses
to stimuli, and the distractor does not contain any form of punishment. This
experiment thus attempts to understand if bees might be able to learn fine
discrimination tasks in an ecologically relevant scenario.
Analysis of bee choices
In the current study, a bee approaching a stimulus had several possible
responses depending upon whether the stimulus was perceived as the target or
the distractor. The bee could make a correct decision and land on the platform
of the target stimulus, or an incorrect decision and land on the distractor
platform. Alternatively, the bee could incorrectly reject the target stimulus,
or correctly reject the distractor stimulus. A rejection was defined as a
clear approach to the stimulus to a distance of less than 10 cm, slowing to
look at the stimulus, and then making a saccadic turn and flying away without
making any contact with the landing platform
(Fig. 2).
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; Green and Swets,
1966; Miller,
1996). To statistically evaluate if bee choices for the target
stimulus could be reliably differentiated from chance performance, data was
tested for normal distribution and then a one sample t-test was used
to compare the d' scores for the bees against a score of 0 that
might be expected for random choices. For convenience percentage
discrimination (correct landings/total landings) is also provided, but all
statistics were computed from d' scores
(Collishaw and Hole,
2000).
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 | (1) |
 | (2) |
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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=–0.633, N=12, P=0.027). For the distractor
stimulus there was not a significant correlation of aborts with increasing
experience (Spearman's =0.344, N=12, P=0.273), although
there was a slight trend of more aborts which may indicate that bees extract
information about both target and distractor stimuli
(Stach and Giurfa, 2005).
The mean frequency of correct choices for landings on the target stimulus (Fig. 1A vs B) in the non-rewarded test was 69.0±8.4% (± s.d.), and the mean d' value for bee responses was 1.19±0.63. The ability of bees to correctly respond to the target stimulus was significantly different from chance (one sample t-test, t=5.987, d.f.=9, P<0.001), demonstrating that the bees could discriminate between the learnt target and distractor stimuli. This finding is also consistent with the last 50 bee responses (Fig. 3A) during conditioning, where the mean correct choice was 71.8±4.9%.
To potentially utilise these discrimination abilities in real-world scenarios, it is necessary that the bees correctly recognise the target stimulus in the presence of novel distractors. In the non-rewarded transfer test, bees were able to recognise the target stimulus from a novel but similar scene (Fig. 1A vs C) with 61.5±5.3% accuracy. The mean d' value for bee responses in the recognition condition was 0.58±0.34, and the ability of bees to correctly respond to the target stimulus was significantly different from chance (one sample t-test, t=5.332, d.f.=9, P<0.001). Thus, bees can resolve between photos of familiar forest scenes and novel, but perceptually similar, sylvan panoramas.
Experiment 2
The mean frequency of correct choices for landings on the target stimulus
(Fig. 1B vs C) in the
non-rewarded test was 70.5±11.9%, and the mean d' value
for bee responses was 1.07±0.55. The ability of bees to correctly
respond to the target stimulus was significantly different from chance (one
sample t-test, t=6.108, d.f.=9, P<0.001),
demonstrating that the bees could discriminate between the stimuli used as
distractors in experiment 1.
In the non-rewarded transfer test, bees were able to recognise the target stimulus (Fig. 1B) from a novel but similar scene (i.e. Fig. 1B vs A) with 70.6±15.6% accuracy. The mean d' value for bee responses in the recognition condition was 1.01±0.52, and the ability of bees to correctly respond to the target stimulus was significantly different from chance (one sample t-test, t=6.214, d.f.=9, P<0.001). This confirms that bees can recognise a familiar stimulus from a novel, but perceptually similar distractor as in experiment 1. The result also indicates that the recognition of the stimulus (as in Fig. 1A) in experiment 1 was not due to some preference by bees for this stimulus, as in experiment 2 bees learn to avoid this stimulus.
Experiment 3
Experiment 3 tested if honeybees could potentially learn complex natural
stimuli in a shorter period of training than was provided in experiment 1 or
2, and to evaluate if bees might be able to learn the task in a context where
the distractor stimulus did not contain any bitter solution. Following
differential conditioning for only 40 responses
(Fig. 4) to the same stimuli as
used in experiment 2 (Fig. 1B vs
C), in the subsequent non-rewarded test bees were able to choose
the target stimulus with 61.9±8.9% accuracy and a mean
d' of 0.69±0.30, which was significantly different from
chance (one sample t-test, t=6.484, d.f.=9,
P<0.001). Thus, building on experiments 1 and 2, experiment 3
demonstrates that bees may learn a fine discrimination task of natural scenes
with a relatively short amount of exposure to the stimuli, and even when the
distractor does not contain any form of punishment. To compare if the results
from experiment 3 differed significantly from experiment 2 (which used longer
training and quinine punishment) d' data was compared with an
independent samples t-test (t=2.189, d.f.=18,
P=0.042). Thus, whilst bees can learn to discriminate complex scenes
in a reasonably short time frame, continuing experience (with punishment) as
in experiment 2 does convey some benefit. The current experiments do not
allow, however, a dissection of the relative contribution of either the
quinine and/or training length.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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), this
study shows that recognition of scenery encountered during flight may be
relevant to how bees learn to visually navigate. This could enable foraging
bees to use complex combinations of visual objects that exist in natural
environments as navigational landmarks. Previous work has shown that bees are
able to navigate maze-like structures if provided with salient visual cues
(Zhang et al., 1996;
Zhang et al., 2000), which
could potentially provide bees with the ability to judge distance based on
number of landmarks en route to flower resources
(Chittka and Geiger, 1995a;
Zhang and Srinivasan, 2004).
This current study shows that experienced bees can potentially use complex
natural scenes as landmarks, even when these are perceptually very similar to
other novel scenes encountered between the hive and feeding sites. Although we
only evaluated one type of complex natural scene (trees in a forest), it is
reasonable to conclude from our findings that bees can potentially use their
vision for a wide variety of natural landscapes that might be encountered
during foraging (Chittka et al.,
1992; Zhang et al.,
2004), or when turning back to look at a feeding site and or nest
(Lehrer, 1991;
Lehrer, 1993;
Zeil and Wittmann, 1993).
It is clear from a number of studies that differential conditioning leads
to significantly better performance in discriminating between perceptually
similar stimuli than absolute conditioning
(Dyer and Chittka, 2004a;
Dyer and Chittka, 2004b;
Dyer et al., 2005;
Giurfa, 2004;
Giurfa et al., 1999;
Stach et al., 2004;
Stach and Giurfa, 2005). The
reasons underlying this could include the ability of the bee brain to learn
relevant dimensions from both target and distractor stimuli
(Giurfa et al., 1999) and/or
the development of attention-like mechanisms
(Dyer, 2007;
Giurfa, 2004). In another
insect model, Drosophila, it has recently been shown that experience
with visual stimuli improves feature extraction from complex visual stimuli,
and that the mushroom body region of the brain is critical in shape feature
extraction (Peng et al.,
2007). Two possible mechanisms by which insects might recognise
visual stimuli include a retinotopic-template strategy and/or the use of
specific features extracted from a scene
(Efler and Ronacher, 2000;
Giger and Srinivasan, 1995;
Horridge, 2005; Stach et al.,
2004; Stach and Giurfa,
2005). In Drosophila
(Dill et al., 1993;
Peng et al., 2007) and ants
(Cartwright and Collett, 1983;
Graham et al., 2007) there is
evidence that these insects use a retinotopic-template strategy, and in bees
there is evidence that individuals use feature extraction, which may develop
into configural type processing with experience
(Stach et al., 2004;
Stach and Giurfa, 2005). There
also exists the possibility that individual insects use different visual
strategies depending upon the context of the task to be solved
(Efler and Ronacher, 2000;
Giurfa et al., 1999;
Stach and Giurfa, 2005), which
is interesting in relation to the changes that occur in Drosophila
visual processing depending upon level of experience
(Peng et al., 2007). In this
study the purpose was to evaluate if bees might be capable of solving a
complex visual discrimination that is relevant to their foraging lifestyle.
With complex scene stimuli, it is difficult to determine what visual strategy
the bee visual system is using to solve the task, but the data is indicative
that bees can solve a task of recognising complex scenes reliably.
For spatial vision discrimination tasks, differential conditioning promotes
bees to learn the entire visual pattern, whereas absolute conditioning
restricts learning to the visual content in the lower regions of stimuli
(Giurfa et al., 1999). This is
consistent with observations that for differential conditioning to complex
stimuli, such as faces, honeybee visual processing is completely disrupted by
stimulus inversion (Dyer et al.,
2005), suggesting the possibility that animals with relatively
simple nervous systems have the potential to use configural type processing to
solve tasks (Stach et al.,
2004; von der Emde and Fetz,
2007). In this study, analysis of the frequency of aborted flights
to either target or distractor stimuli
(Fig. 3B) indicated that
extracting information about the target stimulus were the major visual
strategy used. This is also evidenced by the observation that bees could
recognise a learnt target from perceptually similar novel distractors. This
finding is consistent with previous studies indicating that target stimuli
contain significant visual information that the bees visual system can extract
(Dyer et al., 2005;
Stach et al., 2004;
Stach and Giurfa, 2005).
An important consideration is whether a bee flying in a natural environment
receives sufficient experience with complex visual scenes to enable learning
for navigation purposes. Figs 3
and 4 indicate that the spatial
task of discriminating between the target and distractor stimuli is learnt
well after about 20–40 responses are made, and this is consistent with
the rates with which honeybees learn to discriminate between human faces
(Dyer et al., 2005) or spatial
gratings (Srinivasan and Lehrer,
1988). As a forager, an individual bee typically makes 10–15
foraging bouts per day (Winston,
1987), suggesting that learning a complex visual scene as a
landmark is realistic within the time frame of a bee visiting a particular
flower patch within a forest. In addition, bees may learn a scene faster than
estimated above if there is a voluntary effort to inspect a scene, as has been
previously observed from bees at feeding sites (Horridge, 2005). Optic flow
estimates (Srinivasan et al.,
2000) and landmark discriminations
(Chittka et al., 1995a;
Chittka et al., 1995b;
Collett and Zeil, 1997) are
maximally useful in different types of visual environment (e.g. densely
vegetated vs relatively open fields), and one can hypothesise that
honeybees will take full advantage of these different types of visual
information in achieving a computationally robust representation of the
intended route (Vladusich et al.,
2005). This current study thus demonstrates that bees potentially
have the ability to visually learn to discriminate similar complex natural
scenes that could be used as `landmarks' even in a dense forest type scenario
where there are no salient references.
In addition to showing that bees are capable of recognising complex visual
scenes, the data in this study also indicate that signal detection theory is
useful in quantifying the decision making of bees. In particular,
Fig. 2 and
Fig. 3B show that rejection of
stimuli, in addition to landing choices, is an important component of the
decision making process by honeybees and it is thus useful to record these
events for on optimal analysis. This is potentially a powerful analysis
technique for understanding the factors determining invertebrate decision
making (Lynn et al., 2005).
Studies on bumblebee colour learning and evidence of peak shift discrimination
suggest a dynamic behaviour where the bee brain learns to make decisions based
upon level of experience with perceptually similar targets and distractors
(Lynn et al., 2005).
Consistent with their application of signal detection theory for cognitive
learning, the present study reinforces the idea that the learning process is
dynamic and involves multiple possible outcomes which the bee brain can manage
to sort through to solve complex tasks. Understanding this process can, in
turn, provide a more direct route for understanding the mechanisms used by
insects to solve complex visual tasks, potentially improving the design of
semiautonomous machines capable of operating in demanding visual environments
(Franceschini et al.,
2007).
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Acknowledgments |
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