Visual learning in individually assayed Drosophila larvae
1 University of Würzburg, Department of Genetics and Neurobiology,
Biocentre Am Hubland, D 970 74 Würzburg, Germany
2 University of Fribourg, Department of Biology and Program in Neuroscience,
Ch. du Musée 10, CH 1700 Fribourg, Switzerland
* Author for correspondence (e-mail: bertram.gerber{at}biozentrum.uni-wuerzburg.de)
Accepted 23 September 2003
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Key words: Drosophila, larva, vision, learning, taste
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Recently, a number of studies have focused on larval Drosophila,
probably because they have ten times fewer neurons than adults (e.g.
Busto et al., 1999;
Hassan et al., 2000
;
Heimbeck et al., 1999
; Liu et
al.,
2003a
,b
;
Python and Stocker,
2002a
,b
;
Scott et al., 2001
). For
example, comparing larva to adult, the number of receptor neurons within each
hemisphere is 12 versus 6000 for vision, 21 versus 1300 for
olfaction and 80 versus 650 for taste (Stocker,
1994
,
2001
) (for an overview, see
Fig. 1A-E). Relatively little,
however, is known about associative learning in Drosophila larvae.
This is unfortunate, as our knowledge concerning the physiological mechanisms
of synaptic plasticity, which are commonly thought to underlie behavioral
plasticity, largely derives from experiments in the larva
(Koh et al., 2000
). Previous
learning experiments on larval olfactory learning were performed using en
masse assays (Aceves-Piña and
Quinn, 1979
; Heisenberg et
al., 1985
; Tully et al.,
1994
; Dukas, 1998
),
which preclude a combined behavior and physiology approach, because too many
animals are needed to yield learning effects. In this study, therefore, we
used individually assayed larvae and established a visual learning paradigm.
In contrast to Aceves-Piña and Quinn
(1979
), Heisenberg et al.
(1985
) and Tully et al.
(1994
), we used gustatory
stimuli rather than electric shock as reinforcement, largely because the
reproducibility of electric shock learning is compromised
(Forbes, 1993
; F. Python,
personal communication); also, gustatory reinforcement, rather than electric
shock, seems biologically relevant for larval Drosophila.
|
Using visual stimuli and gustatory reinforcement, we can demonstrate for
the first time visual associative learning in Drosophila larvae;
furthermore, this study is the first to demonstrate appetitive larval
learning. The current paradigm, together with its concurrently developed
olfactory companion study (Scherer et al.,
2003), thus opens up the possibility of comparing the organization
of visual and olfactory memories in a simple and genetically
easy-to-manipulate nervous system.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Larvae
We used Canton-S wild-type strains from two stock collections, either
Fribourg (CS-F) (Experiments 1, 3), or Würzburg (CS-W) (Experiments 2, 4,
5). All flies were kept in the Würzburg facility in mass culture
maintained at 24°C, 60-70% relative humidity and subjected to a 14 h:10
hlight:dark cycle. Daily, adult flies were transferred from their current into
a fresh food vial where they were allowed to lay eggs for 24 h. At 115 h after
commencement of the egg-laying period, experiments were begun; experimental
larvae were therefore aged 91-115 h, in some cases even 122 h after egg lay
(AEL). In a companion study (B. Gerber, S. Scherer, M. Kretz, R. F. Stocker,
and M. Heisenberg, manuscript in preparation), we found no effect of age (i.e.
67-91 h, 91-115 h or 115-139 h AEL) on the larval photoresponse (but see
Sawin-McCormack et al.,
1995).
Our procedure of larval staging is admittedly coarse; still, exact staging does not seem to lead to altered or to less variable learning scores, at least in the olfactory version of our paradigm (T. Hendel, unpublished data).
On experimental days, a spoonful of food substrate containing larvae was taken and transferred to a small glass vial. From there, individual animals were removed using a paintbrush, briefly washed in tapwater, and immediately placed into the experimental arena. Thus, in contrast to the procedures used for larval harvest in mass assays, animals were taken exclusively from the food, not from the wall, in order to reduce the likelihood of harvesting wandering stage larvae.
Experimental conditions
Test plates
Agarose (1%; electrophoresis grade, Roth, Karlsruhe, Germany) was boiled in
a microwave oven and allowed to cool down for 30 min, with constant gentle
stirring. Petri dishes (9 cm inner diameter; Sarstedt, Nümbrecht,
Germany) were then filled with a thin layer of agarose. The agarose was
allowed to solidify for 20 min under a protective mesh. Then, lids were put on
the plates to avoid drying out and plates were stored at room temperature for
use as test plates until the following day.
Training plates
As a potentially negative gustatory reinforcer we used quinine hemisulfate
(QUI; purity 92%; Sigma, Steinheih, Germany) or sodium chloride (NaCl; purity
99%; Roth, Karlsruhe, Germany) and as a potentially positive reinforcer,
fructose (FRU; purity 99%; Sigma). These reinforcers were added to the agarose
10 min after boiling to reach final concentrations of 0.2% QUI, 4 mol
l-1 NaCl and 1 mol l-1 FRU. Petri dishes with 5 cm inner
diameter were used to prepare these training plates.
The experimental room was dark except for the experimental light sources; room temperature ranged from 21-25°C. We used cold-light sources with a homogeneous emission spectrum but no UV or IR emission (Intralux 6000 in combination with the '5'' backlight' light table; VOLPI, Schlieren, Switzerland). The Petri dishes were placed in Perspex trays such that the bottom of the dish was elevated 5 mm above the surface of the light table. To shield parts of the Petri dish from light, we inserted black cardboard glued to a transparent foil between the light source and the tray. The cardboard was 3 mm above the light source and 2 mm below the Petri dish. Between the light source and the cardboard, a 1 mm thick aluminum shield was inserted to prevent heating of the Petri dishes and of the cardboard covers. Thus, the 'layers' of the setup were: light table, air, aluminum shield, tranparent foil with/without cardboard, air, Petri dish.
For training, the light table was divided into an illuminated and a dark half, so that the entire training plates could be placed onto either the illuminated or the dark part of the light table. To generate a choice situation during test, we used an assay with two quadrants illuminated and two quadrants dark ('X-plate').
Training and test in Experiments 1, 2
Animals underwent either Light+/Dark- or Light-/Dark+ training. Each
training trial lasted 1 min. For one half of the animals we started with Dark,
for the other half with Light; also, we started with the positive reinforcer
for half of the animals, and with the negative reinforcer for the other half.
This procedure, together with the reciprocal design of the experimental
regimes, precludes non-associative contributions to test performance.
Three larvae were transferred to the center of a training plate using a paintbrush; the training plate contained one of the reinforcers and was exposed to one of the visual conditions (e.g. Light+). Then, the lid was closed and the larvae were allowed to freely move for 1 min. The larvae were then immediately transferred to a second assay plate containing the other reinforcer and exposed to the alternative visual condition (Dark-). This cycle was repeated ten times. Fresh plates were used for each trial.
After training, each larva was individually tested for its light preference in the X-plate assay (see below for details); this was done on a separate, fresh test plate, which did not contain any reinforcer. Thus, animals were trained in small groups of three, but tested as individuals.
Animals from both training regimes were trained alternately. On half the days, we started with animals from the one, and on the other half of the days with animals from the other training regime.
To avoid bias, the identity of the reinforcer was coded before experiments, so that the experimenter was 'blind' with respect to the identity of the reinforcers; these identities were decoded only after the experiment.
Modifications for 'absolute' conditioning in Experiment 5
In Experiment 5, three of the five pairs of reciprocal groups were trained
in an 'absolute conditioning' procedure. That is, in these groups only one
reinforcer was used during training. In an attempt to speed up data
acquisition, all animals in Experiment 5 were trained as groups of eight
animals instead of three, and tested individually in a down-sized version of
the X-plate using Petri dishes with 5 cm inner diameter. Furthermore, we used
2 mol l-1 instead of 1 mol l-1 FRU. All other details
were as specified above.
Behavioral measures and data analysis
For the test, each larva was individually placed in the middle of a test
plate, the lid was closed and the larva could then freely move between
illuminated and dark quadrants. The position of the larva, as defined by the
position of its mouth hooks, was scored every 10 s for 5 min as being in Light
or Dark.
The test performance is presented in three steps, described below and illustrated in Figs 3A-C and 4A-C.
|
|
(A) For a time-resolved description of the animals' performance, we present the percentage of larvae in Dark for each time point as:
% in Dark = (animals in Dark/total animals) x 100.
Thus, a value of 100% indicates that all larvae were recorded in a Dark quadrant, 0% indicates all were in a Light quadrant and 50% indicates equal distribution.
(B) We calculated a preference value for each individual as:
Dark PREF = (counts in Dark - counts in Light) / total counts.
Thus, positive values indicate a dark preference of a given individual and negative values a light preference. In this calculation, temporal resolution is lost. The PREF values of the animals from a given training regime are then represented by box plots. To statistically test for associative learning, we compared these dark preference values between training regimes; as individuals from both training regimes were trained and tested alternately, we could pair them and used the Wilcoxon signed rank test for paired samples; all conclusions remain unaltered if Mann-Whitney U-tests or either paired or unpaired t-tests are used. As argued below, the comparison of reciprocally trained animals and hence the conclusion regarding associative learning is unaffected by baseline preferences for Dark or Light.
(C) To quantify learning performance and to compare learning performance
between experimental conditions, we calculated a learning index (LI) for the
paired individuals as:
![]() |
If a larva left the agarose and climbed onto the lid of the Petri dish before the end of the 5 min observation period, data collection for that animal was stopped at that time point.
Tests for sensitization in Experiment 3
To test whether gustatory stimuli like FRU, QUI or NaCl can
non-associatively modulate the light response, we tested the light response in
the presence of these stimuli; procedures and data analysis were as detailed
above for the test, except that (i) no training was given, (ii) in different
sets of individuals, the test plates were made from PURE agarose or in
addition contained gustatory stimuli. The first part of Experiment 3
(Fig. 5A,B) was designed to
match the gustatory stimuli used in Experiment 1, so we used 1 mol
l-1 FRU and 0.2% QUI and performed the experiment with CS-F. In
addition, we used 1 mol l-1 sucrose (SUC; purity 99%; Roth) and 2
mol l-1 NaCl (purity 99%; Roth). In the second part of Experiment 3
(Fig. 5C), we wanted to match
the conditions for Experiment 4, and therefore used 2 mol l-1 FRU
and 4 mol l-1 NaCl as well as CS-W in the down-sized X-plate
assay.
|
Scanning electron microscopy and histology
For scanning electron microscopy (SEM), larvae were rinsed five times in
water, cooled to immobility, and the last segment cut off. Then, larvae were
fixed overnight in 6,25% glutaraldehyde with 0.1 mol l-1
Sörensen phosphate buffer (pH 7.4). Fixed specimens were washed five
times in buffer for 5 min each and dehydrated through a graded series of
acetone. After critical-point drying in CO2 (BALTEC CPD 030;
Schalkshühle, Germany), larvae were mounted on a table and sputtered with
Pt/Pd (BALZERS UNION sputter; Schalkshühle, Germany). Specimens were
viewed using a scanning electron microscope (Zeiss DSM 962, Oberkochen,
Germany).
To visualise larval neuroanatomy, the GAL4 driver line MJ94
(Joiner and Griffith, 1999)
was crossed with UAS-lacZ (Brand and
Perrimon, 1993
). F1 third instar larvae were dissected
in Millonig's buffer, fixed in 1% glutaraldehyde (in Millonig's), washed and
stained for ß-galactosidase activity with 5-10 mg X-Gal ml-1
dimethyl sulphoxide (DMSO).
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Experiment 2
Visual learning also occurs in another wild-type strain, as shown in
Fig. 4 for CS-W. After
Light-/Dark+ training, animals are more often observed in a dark quadrant
(Fig. 4A) and show a higher
dark preference than animals that had received Light+/Dark-training
(Fig. 4B; P<0.0001,
Z=-5.7); furthermore, the median LI of 0.18 is significantly above
chance level (Fig. 4C;
P<0.0001).
Interestingly, although animals from CS-F and CS-W strains differ in the time course of performance and in overall dark preference (Figs 3A, 4A), the associative learning effect as measured by the LI is quite similar (Figs 3C, 4C; U=3738; P=0.79).
Experiment 3
Next, we report a sensitization experiment. This is interesting because the
above learning experiments were designed to provide a pure measure of
associative learning; i.e. any contribution of non-associative learning to the
LI (e.g. sensitization) is precluded. The fact that sensitization cannot
contribute to the LI does not, however, mean that sensitization cannot occur.
For example, FRU might increase overall dark preference ('stay in this
substrate'), whereas NaCl or QUI might have the opposite effect. We
specifically asked whether gustatory stimuli might have non-associative
effects on the visual response. This is not the case, as the photoresponse is
statistically indistinguishable on PURE agarose and in the presence of 1 mol
l-1 FRU, 1 mol l-1 SUC, 2 mol l-1 NaCl, or
0.2% QUI (Fig. 5B;
P=0.40, H=4.04, d.f.=4). Thus, in CS-F the same gustatory stimuli
that can support associative visual learning (Experiment 1; 1 mol
l-1 FRU and/or 0.2% QUI) do not modulate the photoresponse in a
non-associative way.
Experiment 4
We repeated this sensitization experiment under conditions that match the
following learning experiment, which used CS-W doubled concentrations of FRU
and NaCl (Experiment 5, Fig. 6)
and a down-sized version of the X-plate assay. We compared the photoresponse
on PURE agarose with the photoresponse on 2 mol l-1 FRU and 4 mol
l-1 NaCl and found no statistically reliable differences
(Fig. 5C; P=0.70,
H=0.68, d.f.=2). Thus, even 2 mol l-1 FRU and 4 mol l-1
NaCl do not modulate the photoresponse in a non-associative way. This
underlines the purely associative interpretation of the LIs.
|
Experiment 5
As next step, the reinforcement effectiveness of FRU, QUI, and NaCl was
investigated. As shown before, the combination of FRU and QUI could be used
effectively for reinforcement (Experiments 1, 2). This leaves open the
question of whether FRU or QUI alone would be sufficient to support learning.
Thus, using CS-W, we found that the combination FRU/QUI and FRU alone could
both effectively support associative learning
(Fig. 6; P<0.0001
and P<0.005, respectively); QUI alone, however, did not
(Fig. 6; P=0.10).
Interestingly, the LI values for the combination FRU/QUI and for FRU alone
were statistically indistinguishable (Fig.
6; P=0.42, U=6837.5). Thus, FRU but not QUI is
an effective reinforcer for visual associative learning in the
Drosophila larva.
The same results emerged for 4 mol l-1 NaCl. That is, the combination FRU/NaCl effectively supported associative learning (Fig. 6; P<0.05) whereas NaCl alone did not (Fig. 6; P=0.49). Also, the LI values for the combination FRU/NaCl and for FRU alone were indistinguishable (Fig. 6; P=0.63, U=6578.0). These results confirm that FRU is an effective reinforcer for visual associative learning in the Drosophila larva and suggest that NaCl is not, and are backed up by a statistically significant overall difference between the five groups (Fig. 6; P<0.05, H=18.75, d.f.=4).
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The current paradigm requires relatively few (20 trials) and short (20 min)
training with few (approx. 70) animals, and is similar to a concurrently
developed olfactory learning paradigm
(Scherer et al., 2003). It
requires, however, about an order of magnitude fewer animals than needed for
adult olfactory learning using en masse assays. The short training
time and the need for only a few animals might make this system suitable for
electrophysiological approaches (Koh et
al., 2000
), in vivo imaging
(Fiala et al., 2002
;
Liu et al., 2003b
), and
approaches combined with the MARCM technique
(Lee and Luo, 2001
), or laser
ablation (Schmucker et al.,
1994
). The cellular simplicity of the larval nervous system will
hopefully facilitate these kinds of analyses.
Learning is purely associative
The associative nature of the learning process was ensured by a traditional
reciprocal training design. That is, individuals from the two reciprocal
training regimes (Light-/Dark+ and Light+/Dark-) have identical experiences
with visual stimuli and reinforcer; what is different is exclusively the
contingency between them. As we have shown that test performance depends on
this contingency (Figs 3,
4,
6), the conclusion regarding
associative learning is compelling.
The maximal median LI found in our study is 0.2; this is somewhat less but
in the same range as found in three other assays: (i) the concurrently
developed olfactory version of this paradigm
(Scherer et al., 2003), (ii)
larval electric shock olfactory learning with en masse assays
(Heisenberg et al., 1985
;
Tully et al., 1994
; see,
however, Forbes, 1993
) and
(iii) appetitive olfactory learning in adults using sucrose as reinforcer
(Borst, 1983
;
Heisenberg et al., 1985
;
Tempel et al., 1983
;
Schwaerzel et al.
, in press).
Thus, it seems that LI values of about 0.2 are what one can expect for
associative learning in larvae and for appetitive learning in adults.
No evidence for a non-associative modulation of the
photoresponse
As argued above, the experimental design precludes any non-associative
contribution to the LI values. Nevertheless, we tackled the question of
whether gustatory stimuli may non-associatively modulate the photoresponse
(i.e. the PREF values). For example, FRU might appetitively sensitize larvae
and lead to an increased dark preference ('this tastes good - go into this
substrate'), whereas QUI or NaCl might decrease dark preference ('this tastes
horrible - get out of this substrate'). In two series of experiments, we did
not find evidence for any such non-associative effect
(Fig. 5). This conclusion is in
line with the result of Scherer
(2002), who found that prior
exposure to aqueous solutions of FRU or NaCl does not modulate the
photoresponse; it is further consistent with the finding that the olfactory
response is also not modulated by the presence of FRU, QUI, or NaCl
(Hendel, 2003
).
The carrot, not the stick?
The literature on Drosophila learning, including larval learning,
is largely concerned with aversive reinforcers of almost life-threatening
intensity, heat and electric shock being used most frequently
(Heisenberg, 2003; Waddel and
Quinn, 2001; Zars, 2000
). The
implicit rationale seems to be that Drosophila are stupid and
therefore one has to get tough on them.
To our surprise, we demonstrate here that only FRU, not QUI and not NaCl,
is a potent reinforcer. This matches recent results from olfactory learning
that also indicate that FRU, but not QUI and not NaCl, is an effective
reinforcer (Hendel, 2003);
also, in adult flies Le Bourg and Buecher
(2002
) observed QUI to be
ineffective as a reinforcer in visual learning. Thus, although QUI and NaCl
can well be perceived by the larvae
(Heimbeck et al., 1999
;
Hendel, 2003
), appetitive,
rather than aversive, gustatory reinforcement seems to be effective. Given the
biology of larval Drosophila as feeding stages, appetitive
reinforcement with FRU seems to meet the larva's biological obsessions; in
this respect, Drosophila larvae might be regarded as similar to the
honeybee forager with its proverbial desire for nectar. Thus, appetitive
gustatory reinforcers seem biologically plausible and, in this sense,
gentle.
Beyond this ultimate argument, possible proximate reasons for the negative
results concerning aversive gustatory stimuli may be manyfold. For example, it
might be that pharyngeal, rather than external, gustatory sensilla drive the
modulatory, internal reinforcement pathway (see
Fig. 1 for an overview).
Suppose larvae swallow crumbs of FRU-containing agarose, but only to a lesser
extent, QUI or NaCl-containing agarose; FRU rather than QUI and NaCl could
thus drive pharyngeal gustatory sensilla and hence an internal reinforcement
signal. Maybe because of this compromised access, QUI and NaCl are not
effective as reinforcers. Thus, bitter or salty food, rather than quinine or
sodium chloride per se, might serve as a negative reinforcer. Indeed,
we were informed that when using bitter food, larval olfactory learning might
be detectable in an en masse assay using relatively long reinforcer
exposure (F. Mery, personal communication). Interestingly, the majority of
sensory neurons from the larval pharyngeal gustatory sensillae seem to be
retained into adulthood (Gendre et al., in press), so that a similar argument
regarding quinine versus bitter food might apply in adults as well
(Le Bourg and Buecher, 2002;
Mery and Kawecki, 2002
).
Candidate neuronal substrates
In the following, we speculate on candidate cells for visual and gustatory
input, on a localization of visual memory, and on the modulatory neurons to
mediate reinforcement.
Concerning vision, the Bolwig's organ is a prime candidate as it houses all
known larval photoreceptors (Busto et al.,
1999; Hassan et al.,
2000
). Concerning gustatory input, both the non-dome sensilla of
the dorsal organ, the terminal organ, and the ventral organ are candidates, as
they are necessary for gustatory choice behavior
(Heimbeck et al., 1999
; Liu et
al., 2003). However, these external gustatory organs might be specifically
involved in regulating preference and food uptake ('should I stay here and eat
this?'), whereas the internal, pharyngeal sensillae might be involved in
determining the quality of the swallowed food ('should I ever eat this
again?').
Concerning memory localization, it was found in adult Drosophila
that both aversive (electric shock) and appetitive (sucrose) olfactory
memories, specifically memories dependent on the type I adenylate cyclase, can
be localized to the same set of neurons in the mushroom bodies
(Schwaerzel et al., in press;
Zars et al., 2000
). It will be
interesting to see whether appetitive visual memories in larvae are localized
to the mushroom bodies as well. This seems unlikely, however, as in adults
substantial attempts to implicate the mushroom bodies in simple forms of
visual associative learning yielded negative results
(Heisenberg, 2003
); indeed, in
the fly, and as far as we know in any other experimental system, no
localization of a visual memory has been reported to date.
An investigation into the modulatory system(s) that mediate the reinforcing
effect of FRU might be guided by the finding that octopamine, but not
dopamine, is necessary for appetitive olfactory learning in adult flies
(Schwaerzel et al., in press).
That study follows on the analysis of honeybee olfactory learning that
identified an octopaminergic neuron as sufficient to mediate the reinforcing
effect of the sucrose reward (Hammer and
Menzel, 1995
). At least with respect to dopamine, Python and
Stocker (2002b
) described
candidate neurons in the Drosophila larva, providing a starting point
also for the analysis of this system.
Outlook
This study on visual learning in Drosophila larvae complements the
one by Scherer et al. (2003)
on olfactory learning. Together, they offer the possibility for a comparative
analysis of the organization of visual and olfactory memories and their
potential interaction. We hope that the cellular simplicity of the larval
nervous system will be useful for such approaches. In addition, the technical
simplicity of both paradigms (i.e. they do not require elaborate equipment or
technical skill) will hopefully make them easy to implement in other
laboratories. Finally, both learning paradigms use individually assayed
larvae; this will hopefully contribute towards more closely linking behavioral
analysis and physiology. This seems desirable, particularly to relate
behavioral and synaptic plasticity, as the former has so far been largely
analyzed in adults and the latter in larvae.
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Aceves-Piña, E. O. and Quinn, W. G. (1979). Learning in normal and mutant Drosophila larvae. Science 206,93 -96.
Borst, A. (1983). Computation of olfactory signals in Drosophila melanogaster. J. Comp. Physiol. A 152,373 -383.
Brand, A. H. and Perrimon, N. (1993). Targeted
gene expression as a means of altering cell fates and generating dominant
phenotypes. Development
118,401
-415.
Busto, M., Iyengar, B. and Campos, A. R.
(1999). Genetic dissection of behavior: modulation of locomotion
by light in the Drosophila melanogaster larva requires genetically
distinct visual system functions. J. Neurosci.
19,3337
-3344.
Dukas, R. (1998). Ecological relevance of associative learning in fruit fly larvae. Behav. Ecol. Sociobiol. 19,195 -200.
Fiala, A., Spall, T., Diegelmann, S., Eisermann, B., Sachse, S., Devaud, J. M., Buchner, E. and Galizia, C. G. (2002). Visualization of olfactory information in projection neurons using genetically expressed cameleon in Drosophila melanogaster. Curr. Biol. 12,1877 -1844.[CrossRef][Medline]
Forbes, B. (1993). Larval learning and memory in Drosophila melanogaster. Diploma Thesis, University of Würzburg, Germany.
Hammer, M. and Menzel, R. (1995). Learning and memory in the honeybee. J. Neurosci. 15,1617 -1630.[Abstract]
Hassan, J., Busto, M., Iyengar, B. and Campos, A. R. (2000). Behavioral characterization and genetic analysis of the Drosophila melanogaster larval response to light as revealed by a novel individual assay. Behav. Genet. 30, 59-69.[CrossRef][Medline]
Hendel, T. (2003). Appetitives aber kein aversives olfaktorisches Lernen bei Drosophila Larven. Diploma Thesis, University of Würzburg, Germany.
Heimbeck, G., Bugnon, V., Gendre, N., Häberlin, C. and
Stocker, R. F. (1999). Smell and taste perception in
Drosophila melanogaster larva: Toxin expression studies in
chemosensory neurons. J. Neurosci.
19,6599
-6609.
Heisenberg, M. (2003). Mushroom body memoire-from maps to models. Nat. Rev. Neurosci. 4, 266-275.[CrossRef][Medline]
Heisenberg, M., Borst, A., Wagner, S. and Byers, D. (1985). Drosophila mushroom body mutants are deficient in olfactory learning. J. Neurogenet. 2, 1-30.[Medline]
Joiner, M. A. and Griffith, L. C. (1999).
Mapping of the anatomical circuit of CaM kinase-dependent courtship
conditioning in Drosophila. Learn. Mem.
6, 177-192.
Kitamoto, T. (2001). Conditional modification of behavior in Drosophila by targeted expression of a temperature-sensitive shibire allele in defined neurons. J. Neurobiol. 47,81 -92.[CrossRef][Medline]
Koh, Y. H., Gramates, L. S. and Budnik, V. (2000). Drosophila larval neuromuscular junction: Molecular components underlying synaptic plasticity. Microsc. Res. Tech. 49,14 -25.[CrossRef][Medline]
Le Bourg, E. and Buecher, C. (2002). Learned suppression of photopositve tendencies in Drosophila melanogaster.Anim. Learn. Behav. 30,330 -341.[Medline]
Lee, T. and Luo, L. (2001). Mosaic analysis with a repressible cell marker (MARCM) for Drosophila neural development. Trends Neurosci. 24,251 -254.[CrossRef][Medline]
Liu, L., Leonard, A. S., Motto, D. G., Feller, M. A., Price, M. P., Johnson, W. A. and Welsh, M. J. (2003a). Contribution of Drosophila DEG/ENaC genes to salt taste. Neuron 39,133 -146.[Medline]
Liu, L., Yermolaieva, O., Johnson, W. A., Abboud, F. M. and Welsh, M. J. (2003b). Identification and function of thermosensory neurons in Drosophila larvae. Nat. Neurosci. 6,267 -273.[CrossRef][Medline]
Mery, F. and Kawecki, T. (2002). Experimental
evolution of learning ability in fruit flies. Proc. Natl. Acad.
Sci. USA 99,14274
-14279.
Phelps, C. B. and Brand, A. H. (1998). Ectopic gene expression in Drosophila using GAL4 system. Methods: A Companion to Methods in Enzymol. 14,367 -379.[CrossRef]
Python, F. and Stocker, R. F. (2002a). Adult-like complexity of the larval antennal lobe of D. melanogaster despite markedly low numbers of odorant receptor neurons. J. Comp. Neurol. 445,374 -387.[CrossRef][Medline]
Python, F. and Stocker, R. F. (2002b).
Immunoreactivity against choline acetyltransferase, -aminobutyric acid,
histamine, octopamine, and serotonin in the larval chemosensory system of
Drosophila melanogaster. J. Comp. Neurol.
453,157
-167.[CrossRef][Medline]
Rubin, G. M., Yandell, M. D., Wortman, J. R., Gabor Miklos, G.
L., Nelson, C. R., Hariharan, I. K., Fortini, M. E., Li, P. W.,
Apweiler, R., Fleischmann, W. et al. (2000). Comparative
genomics of the eukaryotes. Science
287,2204
-2215.
Sawin-McCormack, E. P., Sokolowski, M. B. and Campos, A. R. (1995). Characterization and genetic analysis of Drosophila melanogaster photobehavior during larval development. J. Neurogenet. 10,119 -135.[Medline]
Scherer, S. (2002). Associative olfactory learning in individually assayed Drosophila larvae. Diploma Thesis, University of Fribourg, Switzerland.
Scherer, S., Stocker, R. F., and Gerber, B.
(2003). Olfactory learning in individually assayed
Drosophila larvae. Learn. Mem.
10,217
-225.
Schmucker, D., Su, A. L., Beerman, B., Jackle, H. and Jay, D. G. (1994). Chromophore-assisted laser inactivation of patched protein switches cell fate in the larval visual system of Drosophila.Proc. Natl. Acad. Sci. USA 91,2666 -2668.
Schwaerzel, M., Monastiroti, M., Scholz, H., Friggi-Grelin, F., Birman, S. and Heisenberg, M. (in press). Dopamine and octopamine differentiate between aversive and appetitive olfactory memories in Drosophila. J. Neurosci., in press.
Scott, K., Brady, R. J., Cravchik, A., Morozov, P., Rzhetsky, A., Zuker, C. and Axel, R. (2001). A chemosensory gene family encoding candidate gustatory and olfactory receptors in Drosophila.Cell 104,661 -673.[Medline]
Sokolowski, M. B. (2001). Drosophila: genetics meets behavior. Nat. Rev. Genet. 2, 879-890.[CrossRef][Medline]
Stocker, R. F. (1994). The organization of the chemosensory system in Drosophila melanogaster: a review. Cell Tissue Res. 275,3 -26.[CrossRef][Medline]
Stocker, R. F. (2001). Drosophila as a focus in olfactory research: mapping of olfactory sensilla by fine structure, odor specificity, odorant receptor expression and central connectivity. Microsc. Res. Tech. 55,284 -296.[CrossRef][Medline]
Tempel, B. L., Bonini, N., Dawson, D. R. and Quinn, W. G. (1983). Reward learning in normal and mutant Drosophila.Proc. Natl. Acad. Sci. USA 80,1482 -1486.[Abstract]
Tully, T., Cambiazo, V. and Kruse, L. (1994). Memory through metamorphosis in normal and mutant Drosophila. J. Neurosci. 14,68 -74.[Abstract]
Waddell, S. and Quinn, W. G. (2001). Flies, genes and learning. Ann. Rev. Neurosci. 24,1283 -1309.[CrossRef][Medline]
Zars, T. (2000). Behavioral functions of the insect mushroom bodies. Curr. Opin. Neurobiol. 10,790 -795.[CrossRef][Medline]
Zars, T., Fischer, M., Schulz, R. and Heisenberg, M.
(2000). Localization of a short-term memory in Drosophila.Science 288,672
-675.