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First published online November 17, 2006
Journal of Experimental Biology 209, 4802-4808 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02574
Lack of generalization of object discrimination between spatial contexts by a bat
1 Max-Planck Institute for Ornithology, Seewiesen, Germany
2 Department of Biology, University of Munich, Germany
Author for correspondence (e-mail:
york.winter{at}uni-bielefeld.de)
Accepted 2 October 2006
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Summary |
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Key words: generalization, object discrimination, learning set, cognition, echo location, two-alternative forced-choice, context specific learning, spatial, bat
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Introduction |
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). This is mediated
by floral odours that are highly attractive to bats
(Knudsen and Tollsten, 1995;
Bestmann et al., 1999; von Helversen et
al., 2000). The combined occurrence of UV-sensitivity in flower
bats (Winter et al., 2003) and
UV-reflectivity of bat flower corollas
(Biedinger and Barthlott, 1993)
also indicates a function of vision in flower detection
(Winter et al., 2005). A bat
may visit the same flower many times per night and such revisits are then
mainly guided by spatial memory (Thiele
and Winter, 2005; Winter and
Stich, 2005).
The importance of echolocation to detect and discriminate flowers is
probably restricted to orientation in the immediate target surroundings. In
the rainforest vine Mucuna holtonii, for example, a uniquely formed
petal (the vexillum) acts as an echoacoustic mirror and `nectar-guide', which
is necessary to successfully attract bat pollinators to single flowers
(von Helversen and von Helversen,
1999; von Helversen and von
Helversen, 2003). Other bat-pollinated flowers are bell-shaped or
of other echoacoustically conspicuous form (for details, see
von Helversen et al., 2003).
Since these features differ with respect to the echoes of leaves or other
objects from surrounding vegetation it has been speculated that such echoes
may facilitate flower detection (von
Helversen et al., 2003).
The echo signal or stimulus a bat receives from a given flower target is a function of this bat's own position in space and angle of echo call generation. Since bats approach targets from flight rather than from a stationary decision platform they ensonify (`view') hitherto unknown objects from unpredictable directions. In this situation, the echo signals resemble so-called physical colours (`metallic colours') in the visual domain that change their appearance with the angle of object illumination and perception. This is caused by spectral interference.
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;
von Helversen, 2004;
Thiele and Winter, 2005).
Glossophaga soricina is also capable of size-independent
generalization of hollow forms that differ in curvature (e.g. hemisphere
vs paraboloid) when training and test stimuli are presented at the
same location (von Helversen,
2004). But will a bat recognize flower shape cues learnt at one
spatial location, when confronted with such flowers at a different spatial
location with a potential change in appearance?
This recognition task is treated as a problem of stimulus constancy in the
classical perception literature. But it may also be regarded as a problem of
stimulus generalization (Ghirlanda and
Enquist, 2003). The same geometric object serving as the signal
source may generate echoes that vary in complex ways if ensonified (`viewed')
from different directions, as compared to stimulus training. While the
physical similarity between objects will likely include familiar components,
which would be a basis for generalization, the change in echo parameters will
not necessarily occur along a simple sensory gradient and thus could be
difficult for the animals to classify.
We examined the following question: do free-flying bats, conditioned in a two-choice task to a positive echoacoustic object stimulus (S+), transfer their stimulus response to a new spatial location? We tested this experimentally by conditioning flower bats at one location to differentiate between a positive (S+) and negative (S-) echoacoustic stimulus. After learning this task bats were confronted with the same discrimination task at a second location. If at the second location they utilized their knowledge of S+ previously acquired, then they should distinguish between S+ and S-immediately, which should be reflected in the proportion of choices for S+. If, on the other hand, they did not transfer their knowledge between spatial locations then there should be no initial preference for the S+ stimulus at the second location.
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Experimental feeders were computer-controlled, equipped with photosensors
at the front to detect the visit of a bat and connected to a stepper-motor
syringe pump for reward delivery. Feeders were also equipped with a motorized
swivel arm for automatic presentation and exchange of echoacoustic stimuli
(see Winter and Stich, 2005).
We employed the two different geometrical objects shown in
Fig. 1: a perforated hollow
sphere (training golf ball) as the positive object and a triple mirror
(three-sided corner reflector) as the negative object - two very different
stimuli with regard to their echoacoustic reflective properties [see
fig.
1(Thiele and Winter,
2005)]. Previous experiments had shown that Glossophaga
can discriminate these stimuli by echolocation
(Thiele and Winter, 2005).
The swivel arm of a feeder carried both the positive and negative object at its opposing ends. The arm's orientation determined which object was presented to the front (Fig. 1). Within a pair one feeder presented the positive (S+), the other the negative stimulus (S-) determined by a random procedure, with a maximum of three consecutive presentations of S+ on the same side. After each choice by a bat, both swivel arms rotated by 90° and then either continued the rotation (change of presented stimulus) or turned back again (previous stimulus presented). This ensured that swivel arm motors did not provide predictive acoustic cues.
Individual feeders within a pair were arranged horizontally, separated by 25 cm and placed about 20 cm in front of a plastic wall. During phase II of the experiments, individual bats had alternating access to two identical pairs of feeders, each programmed as a two-alternative forced-choice paradigm. The first pair of feeders was within the individual cage, the second pair of feeders was within the experimental room. Room feeders were part of a larger feeder array (8x8), whose 62 other feeders were concealed behind a large plastic sheet during the experiment described here. Bats showed no interest in the covered feeders.
To exchange a bat between the cage feeder pair and external feeder pair,
the bat was automatically released from its cage, then searched for nectar at
the external feeder pair within the experimental room, and was locked in its
cage again after the end of a trial at the room feeder pair (see below).
Details and illustrations of this automated experimental set-up are given
elsewhere (Winter and Stich,
2005).
Pretraining
All individuals were already familiar with the automatic feeders and were
habituated to the individual cages used in the experiment. We used two groups
of animals that differed in their previous experience with 2-AFC echoacoustic
discrimination. The six animals in one group (naïve group) had
participated in an experiment using the automated feeders, both in the cages
and in the larger experimental room, about 4 months earlier; however, without
echoacoustic discrimination training
(Winter and Stich, 2005)
(K.P.S. and Y.W., unpublished). The three bats in the other group (experienced
group) had taken part in an experiment immediately prior to the one described
here, in which they had learned to differentiate between rewarding and
non-rewarding feeders on the basis of echoacoustic characteristics in a 2-AFC
paradigm (Y.W. and D. Tafur, unpublished data). In this earlier echoacoustic
discrimination experiment a similar type of feeder was used, but the specific
echoacoustic stimuli employed differed from those in the present study.
Experimental procedure
Experimental phase I
All animals started the experiment in their cages where they learned to
discriminate between the S+ and S-stimulus pair. We used the perforated sphere
as S+ and the triple mirror as S-(Fig.
1). The bats required 1-3 nights and several hundred to 8000
choices until they had learnt this discrimination task.
Experimental phase II
Phase II began immediately after phase I. The animals continued with the
discrimination task from phase I while in their cages. In addition, each
individual left its cage to the feeder pair in the experimental room for up to
five times per night and for time intervals of about 40 min each. The animals
were divided into three groups with three individuals each. All three
individuals from one group performed their individual experiments in parallel
but only a single bat was released into the experimental room at the same
time. Overall, each bat spent about one third of its 12 h night time with the
room feeder pair and two thirds with its cage feeder pair. A bat left its cage
voluntarily to enter the room when its electronic cage door opened, after cage
feeders had been turned off and experimental room feeders turned on. A bat
returned from the room to its cage when the procedure was reversed after the
end of a trial. Details of this procedure allowing series of trials with
multiple individuals without the presence of the experimenter are described
elsewhere (Winter and Stich,
2005). Animals quickly adopted the procedure and we had no
problems running three individuals in parallel. Experimental phase II began
with the first trial at the room feeder pair (see below) and lasted until the
end of the experiment. Experimental phase II lasted 3-4 nights.
Definitions
Experimental phases I and II
See above.
Room feeder trial
A trial began with the first visit to one of the two room feeders and ended
after a total of 200 visits or after 40 min, whichever occurred first.
Cage feeder trial
During phase II, each uninterrupted period that a bat was in its cage was
considered a cage trial. Since the experiments were conducted with three
animals simultaneously with only one single individual released into the
experimental room at a time, a cage feeder trial lasted roughly twice as long
as a trial at the room feeder pair, i.e. about 80 min, and contained a
correspondingly larger number of visits.
Percent correct choices
Correct choices were visits to the S+ feeder (perforated sphere,
Fig. 1). Therefore, `percent
correct choices' equals the number of correct choices divided by all choices.
During phase I, percentages were determined for blocks of 100 choices. During
phase II, one percentage value was determined for single trials, i.e. for
60-200 choices each.
Data analysis
Statistical analysis of the animals' performance was carried out using
generalised linear models (GLM, SAS Procedure Genmod). Since the percentage of
correct choices was calculated from binomial data (correct or incorrect), we
transformed data with a logit link function. The quotient `correct choices/all
choices' was taken as the dependent variable. Individuals were treated as
repeated subjects. We corrected models for overdispersion (SAS dscale
option).
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Influence of previous experience on acquisition of discrimination performance
We had two experimental groups of animals: the naïve group
(N=6) and the experienced group (N=3). Both groups were
exposed to two treatments, here termed experimental phases I and II. We
analysed the data over the first 1000 choices under each condition within a
single generalized linear model comparing groups and conditions. As a general
effect, correct performance increased with the number of trials an individual
had made (GLM trial, Wald 
2=5.87, d.f.=1, P<0.02).
This increase in performance, however, differed between experimental groups
(GLM trialgroup, Wald 2=8.10, d.f.=3,
P<0.05), an effect that we further examined by post-hoc
comparisons using contrasts. In experimental phase I, bats from the
experienced group increased performance significantly faster than individuals
from the naïve group (Fig.
3, Fig. 4A; GLM
trialxgroup, Wald 2=160.14, d.f.=1,
P<0.0001). On the other hand, groups did not differ in their
initial correct choice level (GLM intercept group effect, Wald
2 0.71, d.f.=1, P=0.40). During phase II, the
naïve group increased performance at the room feeder pair faster than
during the previous phase I at the cage feeders (GLM, Wald
2=10.7, d.f.=1, P=0.001). However, during this phase
II there was no difference any more between the two groups naïve and
experienced (Fig. 4B, GLM, Wald
2=0.03, d.f.=1, P=0.86). Since the discrimination
task was identical at both locations it follows that prior experience appears
to accelerate the initial acquisition of the task. Groups `naïve' and
`experienced' did not differ in performance during phase II at the second
location, since by then individuals from both groups were experienced with the
2-AFC paradigm. There was also a trend for the experienced group to learn more
slowly during phase II at the room feeders than during phase I (GLM, Wald
2, P=0.052).
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We found this result astonishing. Among bat-pollinated plant species, at
least the legume Mucuna holtonii utilises differences in the
echoacoustic signature of its flowers to attract bats at the right time. When
nectar is available, a petal, the vexillum, is raised acting as an
echoacoustic triple mirror. Mucuna holtonii flowers without a
functioning vexillum are hardly ever visited by nectarivorous bats
(von Helversen and von Helversen,
1999; von Helversen and von
Helversen, 2003). In this natural setting, glossophagine bats
therefore clearly use the echoacoustic configuration of flowers - as one would
expect - without learning this signature for every flower; in other words,
they generalize. Yet why was this not apparent in the experiment presented
here? Possible explanations are discussed below.
Relevance of echoacoustic generalization
A question at the outset is whether the learning of echoacoustic
generalization is likely to be important to nectar-feeding bats under natural
conditions. Numerous behavioural studies from echolocation research have
examined the psychophysics of echoacoustic stimulus discrimination in bats
(Neuweiler, 2000).
Nevertheless, comparative information on learning ability between members from
different trophic groups is not available. Flower-visiting glossophagines
belong to the so-called `whispering bats' that emit only faint or highly
directional echolocation calls (Neuweiler,
2000). Reduced development of echolocation goes along with the
increased importance of olfaction for flower detection, a very different
sensory modality. The origin of an olfactory cue is more difficult to localise
than an echoacoustic or visual stimulus. On the other hand, the composition or
`shape' of an olfactory stimulus is maintained independent of the angle into
which it propagates or from which it is perceived. This stability in signal
structure should facilitate the recognition of a floral bouquet from a
computational point of view and make such stimuli highly useful for plant
species identification. It would be interesting to know how bats would respond
to olfactory stimuli in our experiments.
Despite the importance of olfaction, echolocation is definitely used to
orient at flowers such as Mucuna or at feeders in the laboratory, at
least within the regional scale of the immediate target surroundings
(von Helversen et al., 2003;
von Helversen and von Helversen,
2003; Thiele and Winter,
2005). The echolocation calls of Glossophagines are high-pitched
and brief, which allows for a good resolution of small structures
(von Helversen and von Helversen,
2003) although probably only from short distance.
Glossophaga is able to generalize between different sizes of hollow
forms differing in curvature in a situation where training and test stimuli
are presented at the same location (von
Helversen, 2004). Similarly, artificial reflectors placed on
flowers in the natural environment are discriminated by bats. Initially
artificial reflectors suppress flower visitation rates, but over time (within
2 nights) naturally foraging bats learn to accept them
(von Helversen and von Helversen,
2003). Thus the ability to recognize and distinguish echoacoustic
objects associated with flowers is evident and relevant also in an ecological
context for flower visiting bats.
Spatial context: 2-AFC conflict with spatial memory
Glossophaga bats in previous laboratory experiments remembered
both the spatial location of a feeder and its echoacoustic characteristics
(Thiele and Winter, 2005).
However, when returning to a profitable feeder the animals oriented primarily
by the spatial cue even if this was in conflict with object information, i.e.
the feeder or flower specific echoacoustic appearance. Thiele and Winter also
observed in the course of an echoacoustic 2-AFC discrimination task that a
highly trained Glossophaga (over 90% correct choices) began to
develop a location preference after only eight consecutive presentations of
the positive object at the same side
(Thiele and Winter, 2005).
These two findings indicate a strong preference of Glossophaga to
orient based on spatial memory rather than by object-cue guidance.
Spatial context specific learning may have interfered with the learning task of the present experiment. During phase II of our experiments, bats were confronted with two 2-AFC setups at different locations: the known setup in the cage, and the novel setup in the room. The nature of the discriminative stimulus pair and also the reward contingency of the 2-AFC paradigm were the same in both locations. We expected bats to have acquired the general factors of the 2-AFC paradigm and thus only be confronted with the generalization problem of recognizing and discriminating S+ and S-stimuli at a new location and possibly from a different flight approach trajectory. This assumption may have fallen short of fully recognizing the learning requirements posed for the bats. Since flower bats use location as a main food predicting stimulus, experimental bats here were confronted with a new set of spatial stimuli at the new location, in addition to a new 2-AFC feeder pair. In a 2-AFC task both left and right positions are rewarded half of the time. If the bats used location as the dominant cue in this experiment, they might initially associate a 2-AFC setup as two distinct spatial locations, each of which irregularly provides food. Eventually, bats must ignore spatial location as a predictor of food and instead restrict attention to the positive object stimulus. In the present study, bats needed several thousand choices (Fig. 4A, naïve) before they learned to ignore spatial location as a predictor of rewards (learned irrelevance). Since flower-visiting bats may be naturally predisposed to experience spatial location cues as salient, learning the 2-AFC paradigm may have been particularly difficult for Glossophaga.
With these considerations in mind, the lack of transferring the disregard
of spatial location within a 2-AFC paradigm to other positions within a room
may not be so surprising after all if we consider the training in the lab
versus in nature. In the lab, the training takes place in one
context, the home cage. There is then no transfer of object discrimination to
a new context, although there is a savings effect, in that the naïve
group learned faster during the second time than during the first. In nature,
the flowers are found in many locations, and discrimination training is thus
distributed over many contexts. The number of instances should promote
learning and generalization of the relevant `concept' (the S+ object). There
is much evidence from learning studies. Pigeons that learn one single instance
of `matching to sample' do not generalize task performance to other cues. But
given many instances of training, transfer to new cases is good
(Wright, 1997;
Kendrick and Wright, 1990).
Niche-specific cognitive strategies?
Concerning the importance of location for orientation during foraging and
the ease with which location as a cue is ignored, flower visiting and insect
eating bats may differ. Insect eaters need to evaluate the environment
constantly (mainly by echolocation) to detect spatially unpredictable prey. In
contrast, flower visitors may rely on the spatial stability of flowering
plants and return to known locations instead of constantly searching by
echolocation: most flowers remain available at least for a single night and
rarely alter their echo acoustic signature. On a more general level this
suggests that the spatial and temporal distribution of food may be
significantly associated with a species' cognitive architecture or its ability
to learn different kinds of tasks. For bats this implies that different cues
(e.g. spatial, visual, echo acoustic, olfactory etc.) may vary in importance
for different trophic groups. Within the trophically diverse leaf-nosed bats
(Phyllostomidae), for example, we would predict that some of the insect-eating
and flower-visiting bats operate at opposite ends of a continuum of food
predictability ranging from the stochastic occurrence of single insects to the
stationary locations of flowers. Fruit-eating bats may be at some intermediate
position. While a fruiting plant can offer resources over an extended time
span, which makes its location worth memorizing, a single fruit is collected
only once. In contrast, a flower with continuous nectar secretion may be
revisited 20 or 30 times during a single night
(Winter and von Helversen,
2001). This hypothesis of cognitive specialisation to trophic
niche dimensions finds support in neuroanatomical correlates. Brain regions
associated with spatial learning such as the hippocampus are largest in
frugivorous and flower visiting bats (Baron et al., 1986;
Hutcheon et al., 2002;
Safi and Dechmann, 2005).
The effect of previous experience on two-choice discrimination
The different prior experience of the two experimental groups allows the
examination of learning performance at the level of a learning set. Both
groups of bats learnt at the same rate the second 2-AFC task during phase II
of the experiment (Fig. 3,
Fig. 4B). In contrast,
experienced bats appeared to learn faster than naïve bats during phase I
(cage, Fig. 3,
Fig. 4A). Apparently, prior
learning experience made learning easier. This supports the idea of the
appearance of a learning set, a general disposition acquired by learning to
solve similar problems (Shettleworth,
1998). An operationally defined learning set can reflect the
operation of many different psychological processes: habituation to the
testing procedures, attention to the relevant stimulus dimensions, learning of
the response-reinforcement contingencies, and so on
(Zeldin and Olton, 1986;
Macphail, 1982). In other words
this could be described as learning how to learn. In this way changes or
improvements in the method of approaching a problem or material to be learned
can arise, allowing more rapid or better learning
(Shettleworth, 1998).
In discrimination tasks, animals not only learn the differentiation
characteristics relevant to the task but also diverse other characteristics of
the environment before they have discovered the relevant ones. Such experience
ought to help them solve the next task with novel stimuli faster, since
attention can immediately be directed to the relevant characteristics
(Shettleworth, 1998). If a
task is presented in a novel environment, however, then this could hamper
performance in an otherwise familiar task. Such could have been the case in
our study. Bats made initially random visits to novel stimuli in a known
environment during phase I, which is the typical situation for any classical
learning experiment. In addition, they also made initially random visits to
known stimuli in a novel environmental context (room feeder pair, phase II).
The individuals with prior experience actually had a tendency to learn more
slowly at the room feeder pair than in the cages
(Fig. 4). Having to master a
novel environmental context could be the reason for such slower learning.
Conclusions
An initial conjunction of spatial context and discrimination learning may
have hindered transfer of object discrimination to a new spatial location.
Alternatively, the bats may have learnt the discrimination task at the room
feeder pair completely anew, and were faster only because of a learning set.
In a new set of experiments to distinguish between these possible
explanations, object discrimination learning on the one hand and 2-AFC
acquisition at multiple locations on the other hand would have to be
dissociated. This could be achieved by first having bats learn the 2-AFC
paradigm at multiple sites, then presenting a new stimulus pair at some of
those sites, and finally confronting them with this already known, new
stimulus pair at the remaining sites where 2-AFC performance has already been
acquired.
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Acknowledgments |
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Footnotes |
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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