Variable rewards and discrimination ability in an insect herbivore: what and how does a hungry locust learn?
1 Department of Entomology, Texas A&M University, College Station, TX
77843-2475, USA
2 Department of Zoology, University of Oxford, South Parks Road, Oxford OX1
3PS, UK
3 Department of Psychology, California State University-Fresno, Fresno, CA
93740-8019, USA
* Author for correspondence (e-mail: s-behmer{at}tamu.edu)
Accepted 28 June 2005
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Summary |
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Key words: associative learning, choice behaviour, insect learning, locust, Schistocerca gregaria
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Introduction |
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Acridids, like honeybees, exhibit both aversion (e.g. Lee and Bernays,
1988,
1990
;
Champagne and Bernays, 1991
;
Behmer et al., 1999
) and
appetitive learning (e.g. Bernays and
Wrubel, 1985
; Simpson and
White, 1990
; Raubenheimer and
Tucker, 1997
) and have highly developed sensory capacities and
motor skills (see Uvarov,
1966
; Chapman and Joern,
1990
; Burrows,
1996
; Chapman,
2003
), which have been examined in great detail (reviewed by
Burrows, 1996
). Acridids,
however, offer some unique advantages over honeybees. For instance, their
nutritional physiology has been investigated in great detail (reviewed by
Simpson and Raubenheimer,
2000
), which permits a broader interpretation of learned behaviour
related to food acquisition, and they readily eat synthetic foods, which
allows for the testing of nutrient-specific appetitive learning. They are also
hemimetabolous, which allows for testing both within and across developmental
stages, and since they are diverse, opportunities exist to explore how
natural-history traits (e.g. specialist vs generalist feeders,
solitary vs gregarious individuals) influence learning abilities.
In this paper, we present a novel protocol specifically designed for acridids that allows learning behaviour, as recorded by changes in choice as well as response latency, to be measured. Response speed, although a common measure of learning in vertebrates, has not proved a sensitive measure within invertebrate models and has yet to be evaluated in acridids. This paper describes experiments using gregarious desert locusts (Schistocerca gregaria) run in a specially designed two-sided Y-maze with arms discriminated by colour or odour and rewards differing in amount of fresh wheat grass or artificial diets with different concentrations of protein and carbohydrate.
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Methods and Results |
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Before proceeding to our first experiment, a brief note concerning the structure of this section is warranted. For each experiment, we present methods followed immediately by the results.
Experiment 1: testing colour and amount discrimination
Identifying test subjects
To standardise nutritional state and levels of motivation in our
experimental test subjects, a selection protocol was employed. Prior to each
individual test, an initial group of 10 newly moulted locusts was collected
(day 0) and fed seedling wheat and wheat germ until the early evening of day
1. On the morning of day 2, usually around 09.00 h, each of the 10 locusts was
given a small piece of wheat (approximately 2-3 mg), followed by another
similarly sized piece 1 h later (10.00 h). We recorded the time at which this
second piece was eaten, and then 5 min later presented the locusts with
another small piece of wheat. This pattern was followed until at least two
individuals had eaten 10 pieces of wheat. These two locusts were then given
food ad libitum until 16.00 h, and all other locusts were returned to
the rearing culture. On the morning of day 3, at approximately 09.00 h, our
two test locusts were given a small piece of wheat (2-3 mg), and we recorded
when it was eaten. Approximately 1 h later, a second piece of wheat was
presented to each locust. Of these two locusts, we selected for testing the
one that was first to eat both pieces of wheat. In the case of a tie, we
selected the one that ate more quickly during the previous day. Our test
insect was then transferred to our experimental test arena.
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The arena itself was placed inside a larger platform that had sheets of white bench-coating paper covering both the sides and back. Extending down the front of the arena was a white cloth sheet, containing a small viewing window (17x9 cm). Two fluorescent lights (Sunglo 20 W, 24/58.98 cm, 1230 lumens, 125 lux; Rolf C. Hagen, Inc.; http://www.hagen.com/uk/) ran lengthwise inside the top of the platform, which ensured that light spread evenly within the platform (measured at 242 lux, using a TES 1330A Digital Lux Meter; http://www.tes.com.tw/). Finally, a pulley system was erected across the top of the platform, with colour-coded handles running out from both sides of the viewing platform, which allowed us to raise and lower all six gates independently of one another.
Arms and rewards
We created two different coloured arms by wrapping the Plexiglas sleeves
(12.5x5.7x5.7 cm) in cellophane paper (green or yellow), and, in
doing so, special care was taken to match their relative luminance (green=164
lux; yellow=182 lux). Inside each arm, near their centres, was a small,
moistened piece of cotton wool, on top of which we placed either one or four
pieces of wheat (each piece approximately 5 mm in length). Henceforth, we
categorise large rewards as being `positive' and small rewards as being
`negative' (negative implying less quantity or quality, not the aversive
nature of the reinforcement). The wheat was placed on the cotton wool so that
it faced away from the entrance and could not be seen until the locust was
inside an arm. Over the course of an experiment, the number of wheat pieces
associated with a particular colour always remained constant, but we balanced
the reward size/colour combination across animals.
Behavioural observations
New test insects were always placed in the centre of the arena (with all
gates down) and left for 1 h to acclimate to the new environment. After 1 h,
one green and one yellow arm containing wheat were inserted into both sides of
the arena, and the gates allowing access to these arms were raised, but only
on one side of the arena. Next, we raised the larger gate that was adjacent to
these two arms. By opening the gates in this order, we insured that the locust
was making its choice from a central point of the arena, which lay some
distance from the two arms. At this time, we also began recording the
behaviour and movement of the locust, using the software package The Observer
3.0 (Noldus Information Technology, Inc., Wageningen, The Netherlands). Among
the events we recorded were the time at which a locust entered its first arm
(henceforth referred to as `enter time') and the time from entering the arm to
the point at which it began to eat the food (`approach time'). Once the locust
began to feed, we lowered the gate of the alternative arm. When feeding ended,
we then recorded the amount of time it took for the locust to leave the arm
(`exit time'). Immediately after leaving the arm, we lowered its gate, and,
after the locust had returned to the middle of the arena, we raised the gate
for the other arm. Next, we recorded the enter time, approach time and exit
time for the second arm. By conducting each trial in this manner, we ensured
equal experience with both options during training. Upon leaving the second
arm, the gate for that arm was lowered and we left the locust in the middle
region for a period of 5 min. A second choice, followed by forced exposure to
the alternative, started when we opened the opposite three gates, as described
above. During the next 5-min rest period, the arms were removed and new clean
arms, containing fresh wheat, were attached. In total, we repeated this
sequence nine times for each subject (nine choices, and nine experiences with
the rewards associated with each coloured arm).
Upon completion of training, we allowed the locust to rest in the central region for 5 min before conducting a non-reinforced preference test (resistance to extinction test). For this test, there was no food in any of the arms, and we raised all of the gates simultaneously, so that the locust had access to all four arms (two green, two yellow). We recorded, over a 20-min period, which arms were entered and for how long locusts stayed in a particular arm. We also recorded the combined amount of time locusts spent in the middle region of the arena.
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In addition to choice behaviour, we were also concerned with the latency of three activities: enter time, approach time and exit time. To test for differences in response latency (1) over the course of training, (2) between the positive and negative stimuli and (3) between the two colours, we used a repeated-measures analysis (RMA) where trials and stimulus were treated as within-subject factors and colour was treated as a between-subject factor (SPSS version 11.5; SPSS Inc., Chicago, IL, USA). When the assumption of sphericity was violated (epsilon value >0.70), we employed the Huynh-Feldt correction procedure. For each latency measurement, data from all nine choice-trials were analysed.
We first examined the mean natural log latency of the entering time for the positive and negative colour and found a significant trials effect (F8,80=2.84, P=0.008). As seen in Fig. 3A, the trend was for locusts to enter the arms more quickly over the course of training. We did not, however, detect a trials x colour (F8,80=1.15, P=0.342) or trials x stimulus interaction (F8,80=1.20, P=0.307). We did, however, find a significant stimulus x colour interaction (F1,10=6.41, P=0.030). The data showed that locusts entered yellow-positive arms much faster than yellow-negative arms, but that entry times into green arms were similar regardless of the reward size.
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The final latency measure, exit time, also showed a significant trials effect (F8,80=5.57, P<0.001), with locusts staying in the arms for shorter lengths of time after they completed feeding (Fig. 3C). We also detected a significant stimulus effect (F1,10=15.86, P=0.003), with locusts remaining in the positive arms longer than the negative arms, but no significant stimulus x trials interaction was observed (F8,80=0.34, P=0.950). There was a significant stimulus x colour interaction (F1,10=16.01, P<0.001). For locusts in green arms, the exit time was similar regardless of the stimulus (negative or positive), but locusts in the yellow arms were more reluctant to leave the positive arms compared with the negative arms.
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Experiment 2: testing odour and amount discrimination with reversal
Identifying test subjects
The method for identifying test locusts was similar to that used in
experiment 1, except that at the end of day 2 we transferred our test locusts
to the test arenas, where they remained overnight, without food.
Arms and rewards
To generate distinctive odours, we placed a small volume (1 µl) of an
essential oil (Culpeper Ltd, London, UK), containing either peppermint
(Mentha piperita) or lemon grass (Cymbopogon flexaoxus), on
a small wad of cotton wool that fitted snugly into a 1.75 ml Eppendorf tube.
The top and bottom of the Eppendorf tube were removed, creating an open tube,
and the tube was attached to the roof of each arm (towards the back). As in
experiment 1, we placed one or four pieces of wheat (negative and positive
rewards, respectively) on a moistened piece of cotton wool in the centre of
each arm. Likewise, over the course of an experiment, the number of wheat
pieces associated with a particular odour always remained constant, and the
reward/odour combination was balanced across test locusts.
Behavioural observations
The protocol used for the fist nine runs of the odour experiment was
identical to experiment 1. After the ninth trial, however, we reversed the
odour-reward combinations for an additional nine trials, rather than run an
extinction test. Our aim was to record how choice preference and response
latency were affected by switching the odour-reward combinations.
Results
In the odour experiment we asked two questions: (1) what is the effect of
large and small rewards on odour discriminations, which is analogous to the
colour discrimination experiment, and (2) what is the effect on performance of
reversing the rewards. Fig. 4
shows the proportion of choices of the odour associated with a positive reward
(Trials 1-9), followed by the proportion of choices of the same odour after
the original reward-odour combination was reversed (Trials 10-18). If locusts
were capable of reversal learning, we would expect them to show, during Trials
10-18, an increased preference for the odour associated with the negative
reward during Trials 1-9. Locusts showed no initial stimulus bias (eight
locusts selected lemon grass first, while four selected peppermint) but, as in
experiment 1, they showed a strong preference for the positive stimulus over
the first nine trials [t0.05(1),11=3.92,
P=0.001]. Preference for the initially positive stimulus did decrease
significantly following the reversal [t0.05(2),11=2.45,
P=0.032]. There was no significant difference between choices for
peppermint and lemon grass in either the pre-reversal
[t0.05(2),5=0.79, P=0.465] or the post-reversal
choices [t0.05(2),5=0.28, P=0.788].
Log latencies for enter, approach and exit time were analysed using repeated-measures ANOVA (RMA) with stimulus (positive or negative), trial and pre- and post-reversal blocks being treated as within-subject factors, and odour (lemon grass or peppermint) treated as a between-subject factor. Here, however, we have conducted two separate analyses. The first is restricted to Trials 1-9 so that results could be compared with experiment 1, while the second includes Trials 1-18, which allows us to examine the effect of the reversal.
As seen in Fig. 5A, the locusts' entry into the arms got faster over the first nine trials (F8,80=4.03, P=0.001). No significant stimulus effect, however, was observed (F1,10=4.29, P=0.065), nor was there a stimulus x trial interaction (F8,80=1.21, P=0.305). We also failed to detect an overall odour effect (F1,10=0.02, P=0.883), and there was no stimulus x odour interaction (F1,10=0.308, P=0.591). (Note: odour as a between-subject factor was not significant for either the approach or exit latencies, and for these two latencies it never interacted in a significant manner with stimulus, trials or blocks.)
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Over all 18 trials, for enter time, we found a significant difference between the pre- and post-reversal nine-trial blocks (F1,10=11.58, P=0.007) but no stimulus effect (F1,10=0.84, P=0.425). There was, however, a significant stimulus x block interaction (F1,10=5.88, P=0.036), which suggests the latency to enter a scented arm was affected by reversing reward amounts.
The approach time for the nine pre-reversal and nine post-reversal trials is shown in Fig. 5B. Within the first nine trials, we found that the overall approach time decreased with time (F8,80=7.42, P=0.001) and that locusts approached the positive odour significantly faster than the negative odour (F1,10=44.88, P<0.001). There was, however, no stimulus x trial interaction (F8,80=1.94, P=0.066). When all 18 choice-runs were analysed, a significant difference between the pre-reversal and post-reversal blocks was found (F1,10=14.45, P=0.003), indicating that locusts' approach times got faster over training. There was an overall stimulus effect (F1,10=19.48, P=0.001), and we detected a significant stimulus x block interaction (F1,10=14.32, P=0.004). The significant interaction was due to the fact that the faster approach time in the positive arm in the first nine trials was lost when the rewards were reversed in the second nine trials.
Finally, exit time is shown in Fig. 5C. In the first nine trials, there was an overall trials effect (F8,80=7.85, P=0.001), with locusts leaving the arms faster over successive trials. We did not observe a stimulus effect (F1,10=2.70, P=0.131) nor a stimulus x trials interaction (F8,80=0.57, P=0.802). We also observed a significant difference in exit time between the pre- and post-reversal blocks (F1,10=15.53, P=0.003) and an overall stimulus effect (F1,10=5.14, P=0.047) but no stimulus x block interaction (F1,10=0.69, P=0.427). On average, locusts left the arms faster in the post-reversal block (Trials 10-18) compared with the pre-reversal blocks (Trials 1-9) and, averaged over all 18 trials, they stayed in the positive arms longer than in the negative arms.
Experiment 3: testing odour and amount discrimination with synthetic foods
The aim of this experiment was to test whether locusts could differentiate
between two rewards based on differences in nutrient concentrations. Here, we
used a synthetic diet, which allowed us to control both the ratio and
concentration of nutrients in our test foods.
Test food
Dry synthetic chemical defined foods, similar to those developed by Dadd
(1961) and modified by Simpson
and Abisgold (1985
), were made
that varied in their ratio of protein (p) to digestible carbohydrate (c).
Ratios (in % dry mass) were as follows: p7:c7, p14:c28, p21:c21 and p28:c14.
Previous studies with S. gregaria have shown the p21:c21 diet to be
near optimal for growth and development
(Simpson et al., 2002
), while
the p7:c7 diet contained nutrients in ideal ratios but in suboptimal
quantities. The p14:c28 and p28:c14 diets are themselves nutritionally
suboptimal but, when presented in combination, they are complementary. All the
foods contained 4% essential micronutrients and all except the p7:c7 diet
contained 54% cellulose (the p7:c7 food had 82% cellulose). Digestible
carbohydrate consisted of a 1:1 mix of sucrose and white dextrin, while the
protein contained 3:1:1 casein:peptone:albumin. The diet was suspended in a 1%
agar solution in a dry:wet ratio of 1:4 and presented to individual locusts as
small cubes.
Identifying test subjects
The protocol differed slightly from the previous two experiments because of
the nature of the food. Here, newly moulted locusts were fed one block (2
cm3) of p14:c28 food and one block of p28:c14 food (food was added
or replaced several times during the day to maintain freshness and quantity)
on days 0 and 1. At the end of day 1 (16.00 h), all the food was removed and
the locusts were left overnight. On the following morning, locusts were given
two small blocks of each food, and then 1 h later we observed individual
feeding behaviour. Specifically, we identified the first two individuals to
consume 7-10 total blocks of food. Once identified, these individuals were
given blocks of p14:c28 and p28:c14 food until the end of the day (16.00 h),
at which point the locusts were transferred to the test arenas, where they
remained overnight.
Arms and rewards
The aim of this experiment was to determine how modifying the nutrient
content of the food, as opposed to bulk amount, affected associative learning.
As in experiment 2, peppermint and lemon grass were placed on cotton in
Eppendorf tubes, but for this experiment we used the p7:c7 and p21:c21 food,
suspended in a 1% agar solution, as our rewards (a negative and positive
reward, respectively). Small blocks of food (2 mm3) were placed in
the middle of the arms, but in these runs no cotton wool was used. Over the
course of an experiment the nutrient content associated with a particular
odour remained constant, but we balanced the reward/odour combination across
test locusts.
Behavioural observations
The protocol used for this experiment was identical to that described for
the colour experiment. We conducted a total of nine choice-trials with equated
exposure to each option, culminating in a 20 min non-reinforced preference
test.
Results
The mean proportion of correct choices in the nine choice-runs, plus the
proportion of choices divided by the subjects when peppermint or lemon grass
was the positive stimulus, is shown in Fig.
6. Analyses revealed that locusts showed a significant preference
for the positive stimulus [t0.05(2),11=4.42,
P=0.001] and that odour did not affect choice behaviour
[t0.05(2),5=0.47, P=0.661].
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The approach time is shown in Fig. 7B, and here we found a significant trials effect (F8,80=4.01, P<0.001). The analysis also showed, consistent with the two previous experiments, that locusts approached the food more quickly in the arm associated with the positive stimulus (F1,10=5.70, P=0.038). There was, however, no significant stimulus x trial interaction (F8,80=1.53, P=0.161).
The mean log latency of the exit time is shown in Fig. 7C. As in the previous two experiments, exit latency decreased over the course of the training trials (F8,80=3.54, P=0.001). The stimulus did not affect exit time (F1,10=0.64, P=0.805), and there was no stimulus x trials interaction (F8,80=1.01, P=0.434).
For the extinction test, locusts made significantly more visits to the arms holding the odour associated with the large reward [t0.05(1),10=2.74, P=0.010]. Overall, locusts made more visits to the arms containing the odour previously associated with the large reward (69.7±7.2%). The number of visits was not influenced by whether the positive odour was peppermint or lemon grass (66.4±9.1% and 72.4±11.4%, respectively). There was, however, no significant difference [t0.05(2),10=0.38, P=0.856] in the amount of time spent in the arms containing the odours previously associated with the positive (338.4 s) and negative stimulus (243.8 s).
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Discussion |
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Choice behaviour is generally considered a good measure of associative
learning (see Bitterman, 1988,
1996
) and, over the first nine
trials of each experiment, locusts showed good choice behaviour with respect
to both amount (experiments 1 and 2) and concentration (experiment 3) of
reward. Choice behaviour was poor, however, during the reversal phase of
experiment 2 (Trials 10-18), which suggests that acridids are slow to
`unlearn' and then `relearn' odour-reward pairings. This finding is in
contrast to work on free-flying insects such as the pipevine swallowtail
(Weiss, 1997
) and honeybees
(e.g. Couvillon and Bitterman,
1985
,
1986
;
Shapiro et al., 2001
), which
tend to exhibit a complete reversal of preference after 10 trials. Perhaps,
with additional trials, locusts would have shown a complete reversal of
preference.
Our experiments also revealed that an acridid's response speed was
sensitive to stimuli associated with greater rewards. For example, although
there were no differences in latency to enter an arm from the centre chamber,
once `surrounded' by the stimulus (approach time), the time to reach a larger
reward was significantly shorter compared with the smaller reward in all three
experiments. This `prospective effect' has been reported in a number of
studies with vertebrates (see Goodrich,
1960; Kraeling,
1961
) and in free-flying honeybees approaching colours and odours
associated with a higher concentration of sucrose solution
(Loo and Bitterman, 1992
). The
current study is, however, the first in which an insect has shown response
latency differences for an option associated with different amounts of a
reward (Couvillon and Bitterman,
1993
). That locusts took significantly longer to exit a coloured
arm associated with a higher reward (retrospective effect) is not unique to
insects, having been found previously in honeybees
(Loo and Bitterman, 1992
).
There are, however, possible alternative explanations for our observed
differences in approach and exit latencies. For instance, after locusts
consumed the larger reward, they may have been more satiated and thus less
motivated to seek food upon entering the arms containing the smaller rewards.
Locusts are known to exhibit quiescence following a large meal (see
Simpson, 1995), but in our
study the larger rewards were in fact small relative to meal size during
ad libitum feeding, so we feel a `satiated' effect is unlikely.
Another possibility is that time delays to the rewards may have influenced
latencies. Locusts were required to `rest' in the middle of the arenas for 5
min before making their first choice, but, after exiting, access to the second
arm was allowed as soon as they returned to the middle of the main arena.
Since locusts often chose the arm associated with the higher reward first, the
time delay for entering that arm would have been, on average, greater than
that for entering the arm associated with the lower reward. Latency, like
choice, could be a function of associative strength, and in vertebrates such
as rats, birds and fish it is considered a good measure of learning
(Mackintosh, 1974
). If latency
is to be considered a good measure of preference in acridids, or any insect
for that matter, our protocol may require slight modifications.
Locusts, with the exception of the number of entries in experiment 3, did
not score particularly well in the non-reinforced preference tests. By
contrast, honeybees show strong response levels (measured as landings on
nonrewarded targets) to stimuli previously associated with greater amount,
concentration, probability or lower variability of reward (see
Bitterman, 1996;
Shapiro, 2000
). This
`resistance to extinction' has also been a good indication of preference in
birds, as measured by cumulative numbers of pecking to a non-rewarding key (M.
S. Shapiro, A. Kacelnik and S. Siller, manuscript in preparation). While an
underlying biological reason might explain why locusts performed poorly in the
non-reinforced tests, the results may also reflect problems with our protocol.
Perhaps our locusts were not given enough time to show preference differences.
For example, Raubenheimer and Tucker
(1997
) used a non-rewarded
preference test that lasted 1 h as the sole measure of preference. An
interesting fundamental difference might exist between acridids and honeybees,
particularly with respect to performance in non-reinforced tests. Resolving
whether this is a perception, learning or performance effect may require
additional work.
Basic associative learning has now been demonstrated in a number of
invertebrates (e.g. fruit flies, cockroaches, Aplysia and crabs; see
Abramson, 1994,
1997
), but by far the greatest
amount of parametric work has been done in honeybees
(Bitterman, 1996
). In many
respects, we found locusts to share much in common with honeybees, but we also
observed some fundamental differences. While comparing and contrasting the
behaviour of acridids and honeybees was one of our goals, an additional aim
was to create a protocol for studying learning in an invertebrate model to
address questions that are not easily studied using honeybees. For instance,
since acridids (as well as other orthopteroids, such as crickets and
cockroaches) are able to independently control the intake of multiple key
nutrients (reviewed by Simpson and
Raubenheimer, 2000
; Behmer and
Nes, 2003
), appetitive learning in response to specific nutrients
can be studied. Certainly, one of the advantages of using acridids is that
they readily consume synthetic foods (e.g. experiment 3). This permits a high
level of control over nutritional content of the test foods but, perhaps more
importantly, it allows researchers to control the nutritional state at the
time learning takes place. Such manipulations open up a number of
possibilities, including exploration of state-dependent learning
(Marsh et al., 2004
;
Pompilio and Kacelnik, in
press
) and risk-sensitive foraging (choices with variability in
reward; see Kacelnik and Bateson,
1996
). Our technique also affords great control over the animals'
experience and timing of rewards, which allows experiments on delay of
reinforcement to be conducted. Delay can be imposed by making the animal wait
for food or by making it travel a greater distance for reward in the presence
of one stimulus compared with another. To date, there is a great amount of
vertebrate literature relating delay of reward to choice behaviour, but, with
the possible exception of Lee and Bitterman's work showing that the delay of a
reward may affect preference for one target over the other
(Lee and Bitterman, 1990
),
this issue has not been explored systematically in invertebrates.
Before concluding, it is worth highlighting some methodological issues as well as commenting on the utility of our approach for comparative studies. First, an initial selection process was used in each experiment. This was done to standardise motivational and activity levels of insects both within and between experiments, not because our testing procedure only worked on a select number of individuals. The selection technique also decreased the likelihood of watching individuals that did nothing, or very little. Second, although locusts learned both colour and odour, we feel that odours are easier to work with and are, from an acridid's standpoint, biologically more relevant. Potential problems with using colours include matching luminescence, overcoming innate biases and having access to a limited spectrum. From a biological perspective, acridids tend to live in a world dominated by shades of green, so they encounter a much narrower range of colour than, for example, free-flying nectar feeders such as butterflies and honeybees. On the other hand, different plants have characteristic smells, and acridids possess an olfactory and nervous system that allows odours to be identified and coded. Thus, odours should be correlated with food types and, compared with colour, should be easier to differentiate and learn. Third, in the artificial diet experiment, locusts received p14:c28 and p28:c14 food prior to testing (days 0-2) but p7:c7 and p21:c21 food during testing (day 3). The foods presented prior to testing were individually suboptimal, but together complementary, which allowed the locusts to self-regulate nutrient intake. During the testing phase of the experiment, novel foods (in terms of nutrient profiles) were presented for two reasons. First, we wanted the locusts to be naïve with respect to the foods they encountered. Second, we wanted the test foods to differ in their nutrient concentration but not their protein:carbohydrate ratios. Finally, one of the strengths of using acridids, or any other orthopteroid, is that their developmental stage is easily determined based on wing pad size, shape and orientation. This means that comparative studies across species are possible because a reliable marker is available that allows a degree of standardisation with respect to age. Acridids and orthopteroids are also easy to sex, which means experiments can control for gender effects.
It is clear from the published literature that parametric analyses of
invertebrate models of associative learning are limited almost exclusively to
honeybees (Abramson, 1997). In
the present paper, we have advocated extending the invertebrate species pool,
because we feel it would shed light on shared processes and phyletic
differences of the learning phenomena not only within invertebrates but also
with vertebrates. We also believe that it would provide a better understanding
of the evolution of learning (Papini,
2002
) and the biological constraints on learning in simple
systems. This will require not merely demonstrating associative learning in
different species but systematically investigating the effects of parameters
of reward such as amount, probability, concentration of metabolites,
variability and timing on different measures of performance. While the
honeybee continues to be a fruitful subject, it also has certain limitations.
Perhaps acridids, especially polyphagous species such as the desert locust
(Schistocerca gregaria) or its close cousin the American grasshopper
(Schistocerca americana), can serve this purpose.
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Acknowledgments |
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References |
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Abramson, C. I. (1994). A Primer of Invertebrate Learning: The Behavioural Perspective. Washington DC: American Psychological Association.
Abramson, C. I. (1997). Where have I heard it all before? In Comparative Psychology of Invertebrates: The Field and Laboratory Study of Insect Behavior (ed. G. Greenberg and E. Tobach), pp. 55-78. New York: Garland Publishing.
Behmer, S. T. and Nes, W. D. (2003). Insect sterol nutrition and physiology: a global overview. Adv. Insect Physiol. 31,1 -72.[CrossRef]
Behmer, S. T., Elias, D. O. and Bernays, E. A.
(1999). Post-ingestive feedbacks and associative learning
regulate the intake of unsuitable sterols in a generalist grasshopper.
J. Exp. Biol. 202,739
-748.
Bernays, E. A. and Wrubel, R. P. (1985). Learning by grasshoppers. Association of colour/light intensity with food. Physiol. Entomol. 10,359 -369.
Bitterman, M. E. (1988). Vertebrate-invertebrate comparisons. In Intelligence and Evolutionary Biology (ed. H. J. Jerison and I. Jerison), pp.251 -276. Berlin: Springer.
Bitterman, M. E. (1996). Comparative analysis of learning in honeybees. Anim. Learn. Behav. 24,123 -141.
Burrows, M. (1996). The Neurobiology of an Insect Brain. Oxford: Oxford University Press.
Champagne, D. E. and Bernays, E. A. (1991). Phytosterol unsuitability as a factor mediating food aversion learning in the grasshopper Schistocerca americana. Physiol. Entomol. 16,391 -400.
Chapman, R. F. (2003). Contact chemoreception in feeding by phytophagous insects. Annu. Rev. Entomol. 48,455 -484.[CrossRef][Medline]
Chapman, R. F. and Joern, A. (1990). Biology of Grasshopper. New York: John Wiley & Sons.
Couvillon, P. A. and Bitterman, M. E. (1985). Analysis of choice in honeybees. Anim. Learn. Behav. 13,246 -252.
Couvillon, P. A. and Bitterman, M. E. (1986). Performance of honeybees in reversal and ambiguous-cue problems: tests of a choice model. Anim. Learn. Behav. 14,225 -231.
Couvillon, P. A. and Bitterman, M. E. (1993). Learning in honeybees as a function of amount of reward: further experiments with color. Anim. Learn. Behav. 21, 23-28.
Dadd, R. (1961). The nutritional requirements of locusts IV. Requirements for vitamins of the B complex. J. Insect Physiol. 6,1 -12.[CrossRef]
Forman, R. R. (1984). Leg position learning by an insect I. A heat avoidance learning paradigm. J. Neurobiol. 15,127 -140.[CrossRef][Medline]
Goodrich, K. P. (1960). Running speed and drinking rate as functions of sucrose concentration and amount of consumatory activity. J. Comp. Physiol. Psychol. 54,560 -565.
Holliday, J. L. and Holliday, N. J. (1995). Changes in learning ability and mechanisms during development of grasshopper nymphs. Melanoplus bivattuatus. Physiol. Entomol. 20,109 -116.
Kacelnik, A. and Bateson, M. (1996). Risk-theories - the effect of variance on foraging decisions. Am. Zool. 36,402 -434.
Kraeling, D. (1961). Analysis of amount of reward as a variable in learning. J. Physiol. Psychol. 53,245 -250.
Lee, J. C. and Bernays, E. A. (1988). Declining acceptability of a food plant for the polyphagous grasshopper Schistocerca americana: the role of food aversion learning. Physiol. Entomol. 13,291 -301.
Lee, J. C. and Bernays, E. A. (1990). Food taste and toxic effects: associative learning by the polyphagous grasshopper Schistocerca americana (Drury) (Orthoptera: Acrididae). Anim. Behav. 39,163 -173.
Lee, Y. and Bitterman, M. E. (1990). Learning in honeybees as a function of amount of reward: control of delay. Anim. Learn. Behav. 18,377 -386.
Loo, S. K. and Bitterman, M. E. (1992). Learning in honeybees (Apis mellifera) as a function of sucrose concentration. J. Comp. Psych. 106, 29-36.[CrossRef]
Mackintosh, N. J. (1974). The Psychology of Animal Learning. London: Academic Press.
Marsh, B., Schuck-Paim, C. and Kacelnik, A.
(2004). State-dependent learning affects foraging choices in
starlings. Behav. Ecol.
15,396
-399.
Menzel, R. and Giurfa, M. (2001). Cognitive architecture of a mini-brain: the honeybee. Trends Cog. Sci. 5,62 -71.[CrossRef][Medline]
Papini, M. R. (2002). Pattern and process in the evolution of learning. Psychol. Rev. 109,186 -201.[CrossRef][Medline]
Pompilio, L. and Kacelnik, A. (in press). State-dependent learning and suboptimal choice: when starlings prefer long over short delays to food. Anim. Behav.
Raubenheimer, D. and Blackshaw, J. (1994). Locusts learn to associate visual stimuli with drinking. J. Insect Behav. 7,569 -575.[CrossRef]
Raubenheimer, D. and Tucker, D. (1997). Associative learning by locusts: pairing of visual cues with consumption of protein and carbohydrate. Anim. Behav. 54,1449 -1459.[CrossRef][Medline]
Shapiro, M. S. (2000). Quantitative analysis of risk sensitivity in honeybees (Apis mellifera) with variability in concentration and amount of reward. J. Exp. Psych. Anim. Behav. Proc. 26,196 -205.[CrossRef][Medline]
Shapiro, M. S., Bitterman, M. E. and Couvillon, P.
(2001). Quantitative tests of an associative theory of
risk-sensitivity in honeybees. J. Exp. Biol.
204,565
-573.
Simpson, S. (1995). Regulation of a meal: chewing insects. In Regulatory Mechanisms in Insect Feeding (ed. R. Chapman and G. de Boer), pp.137 -156. New York: Chapman and Hall.
Simpson, S. J. and Abisgold, J. D. (1985). Compensation by locusts for changes in dietary nutrients: behavioural mechanisms. Physiol. Entomol. 10,443 -452.
Simpson, S. J. and Raubenheimer, D. (2000). The hungry locust. Adv. Study Behav. 29, 1-44.
Simpson, S. J. and White, P. (1990). Associative learning and locust feeding: evidence for a learned hunger for protein. Anim. Behav. 40,506 -513.
Simpson, S. J., Raubenheimer, D., Behmer, S. T., Whitworth, A.
and Wright, G. A. (2002). A comparison of nutritional
regulation in solitarious and gregarious phase nymphs of the desert locust,
Schistocerca gregaria. J. Exp. Biol.
205,121
-129.
Uvarov, B. (1966). Grasshoppers and Locusts, vol. 1 & 2. Cambridge: Cambridge University Press.
Weiss, M. R. (1997). Innate colour preferences and flexible colour learning in the pipevine swallowtail. Anim. Behav. 53,1043 -1052.[CrossRef]