This is a preprint of an article
published in
The Journal of Neuroscience, 2002, 22:6842-5.
Spontaneous vs. Reinforced Olfactory Discriminations
Christiane Linster1, Brett A. Johnson2,
Alix Morse1, Esther Yue1, Michael Leon2
1Department of Neurobiology and Behavior
W249 Seeley G. Mudd Hall
Cornell University
Ithaca, NY 14853
2Department of Neurobiology and Behavior
University of California, Irvine
Room 2205 BS II
Irvine, CA 92697-4550
Abbreviated title:
Neurobehavioral Responses to Enantiomer Odorants
Figures: 2
Acknowledgements:
This research was funded by NIDCD Grant DC03545 to M.L.
Address correspondence to Christiane Linster, Dept. of Neurobiology and Behavior, W249 Mudd Hall, Cornell University, Ithaca, NY 14853; Tel: 607 2544331; Fax: 607 2544308; CL243@cornell.edu.
Key words: Olfactory coding, enantiomers, optical isomers, odor
perception, neural representations, habituation, reinforcement learning,
olfactory bulb, glomeruli.
Abstract
When the major
response domains in the rat olfactory bulb layer that are evoked by odorant
enantiomers are compared, some of these odorant pairs do not show significantly
different activity patterns. Such
pairs are not spontaneously discriminated in a behavioral test. We show here
that even these similar odorants appear to give different activity patterns
when every data point in a glomerular activity array is compared. These odorants also can be
discriminated if they are subjected to differential reinforcement. These data suggest that the method
chosen to assess olfactory discrmination will reveal different olfactory
capabilities of rats. . The small
differences in glomerular activity that probably exist between any pair of
odorants may serve as a basis for odor discrimination when rats are
differentially reinforced, thereby establishing the remarkable limits of rat
olfactory perception. At the same
time, the major differences in glomerular responses appear to serve as the
normal basis for spontaneous odor discrimination.
Introduction
Part of
understanding the olfactory code requires one to be able to predict olfactory
perceptions based on neural representations. To test such predictions, it would
be ideal to use pairs of odorants that have a single
difference in molecular structure that would evoke a small difference in neural
activity. One could then determine
if there was a perceptual difference between the two odorants. A candidate for such molecules would be
enantiomers, which are pairs of odorants that differ only in their
stereoconfiguration. Some, but not
all enantiomer pairs evoke different olfactory perceptions (Leitereg et al.,
1971; Friedman and Miller, 1971; Heth et al., 1992; Taniguchi et al., 1992;
Laska and Teubner, 1999a; 1999b; Laska et al., 1999a; 1999b; Rubin and Katz,
2001; Laska and Galizia, 2001).
We previously reported that the rat olfactory glomerular
responses evoked by the enantiomers of carvone differed significantly, while
those evoked by enantiomers of limonene and terpinen-4-ol did not (Linster et
al., 2001). These data predicted
that rats would discriminate between the enantiomers of carvone but not between
the enantiomers of either limonene or terpinen-4-ol, and we observed exactly
that behavior pattern (Linster et al., 2001). Such data are of interest because they
show that neural responses can be used to predict the perception of the
odorants. These data also are of
interest because they are the first to indicate that rats fail to discriminate
between any two odorants and that the olfactory bulb response does not differ
between any two odorants.
However, we used a novel means to record the behavior of
rats in order to access their perceptions. Specifically, we habituated rats to the (-)-enantiomer and
then determined whether the rats dishabituated to the (+)-enantiomer, or to
other odorants (Linster et al., 2001).
Dishabituation indicated to us that the rats regarded the test odor as
different from the original odor.
This method elicits a spontaneous response based on initial olfactory
perception and thereby differs from the more commonly used differential
reinforcement of one odorant over another to determine whether the odors can be
discriminated after training (Rubin and Katz, 2001; Slotnick, 2001).
We also used a novel means of comparing the olfactory bulb
responses to the odorants (Linster et al., 2001). Specifically, we compared the
maximal 2-DG uptake within previously identified glomerular response domains,
or modules, that have shared responses to odorants (Johnson and Leon,
2000). This method differs from
the more common qualitative reports noting visible differences in glomerular
responses to odorant enantiomers in individual animals (Ma and Shepherd, 2000,
Rubin and Katz, 2001). One
disadvantage of our previous analysis was that it binned many individual
measurements into a few modules for a simplified statistical comparison. Thus, it may have overlooked reliable
differences involving areas considerably smaller than the previously defined
glomerular modules. It therefore
seemed possible that we could reach different conclusions if we compared every
data point in a glomerular activity array, rather
than focusing on modular analyses.
In addition, it seemed possible that differential reinforcement of limonene
and terpinen-4-ol could reveal an ability to discriminate between these pairs
of odorants.
Materials and Methods
Odorants
Enantiomers of limonene, along with
propanal and ethyl isovalerate were purchased from Aldrich Flavors and
Fragrances (Milwaukee, WI).
Enantiomers of carvone and terpinen-4-ol were purchased from Fisher
Scientific/Acros Organics (Pittsburgh, PA). Purities reported by the manufacturers were 98% for
(R)-(-)-carvone, 98% for (S)-(+)-carvone, 95+% for (S)-(-)-limonene, 97+% for (R)-(+)-limonene,
97% for (R)-(-)-terpinen-4-ol, 95% for (S)-(+)-terpinen-4-ol, 98% for ethyl
isovalerate and 97% for propanal.
Odorant exposures for 2-DG uptake were conducted as
reported previously (Johnson et al., 1999). Odorants were volatilized by using high-purity nitrogen gas
bubbled through a 100-mL column of pure liquid in a gas washing bottle at a
flow rate of 250 mL/minute. The
nitrogen stream then was mixed with ultra zero-grade air for a final flow rate
of 2 L/minute (1/8 dilution of odorant vapor. After odorant exposure, rats immediately were
decapitated. Brains were frozen
rapidly in 2-methylbutane at about –45”C and then stored at –70”C
until sectioning.
Mapping
of 2-DG uptake Coronal
sections (20-µm thick) were prepared with a cryostat. Every sixth section was taken for autoradiography, and
adjacent sections were stained with cresyl violet as described previously
(Johnson et al., 1998, 1999). The
stained sections were used both to direct sampling within the glomerular layer
of the autoradiography section and to standardize the rostral-caudal position
of sections in reference to anatomical landmarks (Johnson et al., 1999). Discrete measurements of 2-DG uptake
were directed by a set of radial grids to give samples at about 120-µm
intervals around each section.
Measurements were merged into standardized data arrays covering the
entire glomerular layer (Johnson et al., 1999). Arrays from the two bulbs of each animal were averaged and
then converted to nCi/g 2-DG by using standards exposed to the autoradiography
films. Values in these arrays then
were transformed into z scores prior to statistical analyses (Johnson et al.,
1999).
Statistical
Analyses
Comparisons of patterns of
2-DG uptake were made to examine small differences in 2-DG uptake pattern by
performing t tests at each of the 2,500 locations of z score-standardized
arrays (Johnson et al., 1999). This
procedure is similar to standard analyses used in functional brain mapping
(Hess et al., 2000, Rubin and Katz, 2001, Crespo-Facorro, et al., 2001). We
then constructed a rolled-out map of p values to describe the most reliable
differences in 2-DG uptake across the glomerular layer.
Any point within this data array is roughly aligned with respect to its
position within the bulb, but the absolute size or position within the
glomerular layer is not revealed by this array.
Olfactory discrimination All
behavioral training occurred in a transparent Plexiglas chamber (51x38x25 cm)
divided with a sliding, opaque Plexiglas panel into a start area and a test
area (Cleland, et al., in press; Linster and Hasselmo, 1999; Linster and Smith,
1999). Ceramic bowls (9 cm diameter, 4.5 cm height) were
used to place the odorants and the reward together. At the beginning of each daily training set, a Q-tip was
saturated with a 0.1 ml drop of diluted odorant. The cotton tip was covered
with fine plastic mesh and was then taped to the bottom of the bowl. The bowl then was filled with bedding
(Bed-O-Cobs 0.125 inch laboratory bedding). The reward, a bit of sweetened cereal (KelloggÕs Froot
Loops), was buried in the bedding, which was replaced after every trial.
Shaping. Rats were first shaped to retrieve a
reward by digging through the bedding.
At the beginning of each trial, the rat was placed in the start
area. Two bowls were placed in the
test area, one containing both the cereal reward and the odor, the other
containing no reward and no odor.
When the partition was removed, the rat entered the test area and was
allowed to dig in the bowls until it retrieved the reward. During the first few trials, the reward
was placed on top of the scented bowl, but after several successful retrievals,
the reward was buried deeper and deeper into the bedding. When the rat learned
to dig in order to retrieve the reward, the bowls were moved about in the test
area to force the rat to use the odor to locate the correct bowl. Shaping was considered to be complete when
a rat could successfully retrieve a reward that was deeply buried in the
scented bedding and when the rat would dig even in the absence of a reward.
Behavioral testing We determined whether adult male
Sprague-Dawley rats could learn to discriminate between pairs of isomers: (+)-
and (-)-limonene, as well as (+)- and (-)-terpinen-4-ol. For comparison, we tested the ability
of these rats to discriminate between two pairs of control odorants, ethyl
isovalerate (apple odor) and propanal (unpleasant fruit odor), as well as (+)-
and (-)-carvone, which we had
shown previously to be easily discriminated by rats in our
habituation/dishabituation task.
Because each odorant was only used once, the same rats were used in all
experiments.
During each trial, rats were presented with two bowls, each
containing one of the two enantiomers, but only one of the bowls reliably
containing the reward. The
presentation of the reward was counterbalanced between odorants. Each training set was comprised of 20
consecutive trials with the same two odorants. During each trial, we recorded the bowl in which digging was
first observed, but subjects were left to dig in either bowl until the reward
was retrieved. The trial was
terminated after one minute if the rat did not dig at all. The bedding in the bowls was exchanged
after each trial. In order to
ensure that the rats were learning about the test odorants and not identifying
the cereal reward by its own smell, we presented the rewarded odorant without
the cereal reward on every 5th trial (probe trials). Shortly after the rat registered a preference by digging in
the bowl, the reward was dropped onto the scented bedding to maintain the
association of the odorant with the reward. Rats that did not dig in either bowl on more than one of
these probe trials were excluded from the analysis.
Statistical analysis. Data
analyses were performed using SPSS statistical software on the average number
of correct responses. During each
experiment, some rats had to be excluded because they would not perform the
task on that particular day. A
total of 11 rats were tested on (+)- and (-)-limonene, 10 rats on (+) and (-)
terpinen-4-ol, 13 rats on (+) and (-) carvone and seven rats on the control
odorant comparison. After two-way
ANOVA testing for differences in correct responses to the rewarded odorant,
pair-wise post-hoc tests (Tukey HSD) were performed to determine which odors
induced significant differences in preferences. All tests were two-tailed, and the alpha level was set at
0.05.
Place Figure 1 about here
When z score-standardized arrays of 2-DG uptake evoked by
(+)-limonene were compared to those evoked by (-)-limonene on an individual
position-by-position basis, a number of potentially significant t values were obtained (Fig. 1). The low p values
often were clustered together, a pattern unlikely to occur on the basis of
chance alone. These clusters were
found in a scattered distribution across the entire glomerular surface. Clusters of low p values also were obtained in comparisons of patterns
evoked by (+)-terpinen-4-ol and (-)-terpinen-4-ol. There were locations where
(+)-enantiomers evoked higher uptake than (-)-enantiomers as well as other
areas where uptake evoked by (-)-enantiomers exceeded that evoked by
(+)-enantiomers. It should be
noted that many of these areas of apparently different activity were not
obvious by simple inspection of original activity maps, in contrast to our
previously reported differences in activity patterns evoked by carvone enantiomers
(Linster et al., 2001).
Place Figure 2 about here
Given these small apparent differences in glomerular activity patterns, we considered the possibility that rats might respond differently to these odorants if it were made important for them to do so. We made it important to them by reinforcing their selection of one enantiomer over the other with a sweetened food reward (Linster and Hasselmo, 1999). Indeed, rats rapidly reached the learning criterion of 90% correct responses for discrimination between both limonene enantiomers and terpinen-4-ol enantiomers (Figure 2). In addition, they learned to discriminate between the enantiomers of carvone and between two unrelated odorants. While there were no differences among groups in responses during the first five reinforced discriminations, during trials 6-10, significant differences emerged across the four-odorant set (F(3,37) =10.191, p < 0.001). These differences arose between the carvones and limonene (p < 0.001), between the carvones and terpinen-4-ol (p < 0.02), as well as between the two control odorants and both limonene (p< 0.001) and terpinen-4-ol (p<0.005). The number of correct responses to the enantiomers of limonene and terpinen-4-ol were not significantly different from each other, nor were those between the enantiomers of carvone and the two control odorants. During trials 11-15, small differences across odorant sets persisted (F(3,37)=3.665; p < 0.021) and this difference arose solely between the enantiomers of terpinen-4-ol and the control odors. There were no significant differences observed during the last five trials in overall responses to the four-odorant set. Thus, although rats eventually learned all three enantiomer discriminations, they were slower to learn to discriminate between the enantiomers of limonene or terpinen-4-ol than between the enantiomers of carvone or between the two unrelated odorants.
Discussion
We
previously showed that rats do not discriminate between (+)- and
(-)-enantiomers of either limonene or terpinen-4-ol in a spontaneous
discrimination task (Linster et al., 2001). Now, we report that rats can be conditioned to discriminate
the same odorant pairs with only a few trials involving differential reinforcement
of one enantiomer versus the other.
In our previous modular analysis of glomerular activity patterns, the
enantiomer pairs of limonene and terpinen-4-ol appeared to evoke the same
pattern of activity (Linster et al., 2001). Now, we report that a point-by-point comparison of activity
across the entire glomerular layer can reveal numerous, small areas of
potential difference in the activity patterns evoked by the same enantiomer
pairs. Our data are consistent
with the idea that rats normally ignore small differences in glomerular
activity and use only the major differences in module responses to make
spontaneous perceptual judgments. While
small differences in glomerular activity normally may be ignored, such small
differences may be used to make discriminations if they areare subjected to the
motivational and experiential consequences of differential reinforcement.
Small differences in glomerular activation patterns could
arise from low-affinity responses to one odorant that are not present for the
other odorant. Small differences
in glomerular activity also could result if two odorants were differentially
contaminated with other odorants.
At some level of analysis, all odorants are contaminated with other
odorants or are normally experienced against a odorized background . In most studies on olfaction, where
odorant purities range from 95 to 99.9%, odorant impurities sum to equal 0.1-5%
of the total mass of the odorant preparation. Normal rats easily can learn to identify a mixture of 0.01%
cineole and 0.5% amyl acetate when compared to 0.5% amyl acetate alone (Lu and
Slotnick, 1998). Therefore, it is
clear that rats can perceive the levels of
contaminants that are found in odorants.
One may predict that all odorants (even different preparations of the
same odorant) will generate patterns of glomerular activity with at least small
differences from all other such patterns. Moreover, rats should be able to use
such differences to discriminate between all odorants, given differential
reinforcement. Indeed, we
can find no report that shows rats failing to discriminate between any two
odorants when given differential reinforcement. The major modular responses, however, predict that some
odorants will be judged to be similar and others judged to be different when
rats are asked to make a spontaneous discrimination. In a world in which virtually all odorants are perceived
against a variable background of other odorants that are well within the
detection range of rats, categorical distinctions must normally be accomplished
by ignoring these contaminants.
While the size of the neural representation would be expected to vary
along a continuum, there may be expected to be a point at which the neural
reponse is large enough for rats to respond spontaneously it. Indeed, increasing concentrations of
odorants that humans indicate change in perception with concentration (Arctander,
1994) have been shown to evoke new large responses in
the rat glomerular layer (Johnson and Leon, 2000). On the other hand, rats subjected to differential
reinforcement may use the minor glomerular responses of low levels of
contaminants, or any other difference they can detect, to discriminate between
odorants.
The broadly distributed pattern of small response
differences across much of the olfactory bulb glomerular layer also suggests that it may be futile to lesion major foci in the olfactory
bulb and predict that rats would not be able to discriminate between odorants
if they are reinforced for their choice (Lu and Slotnick, 1998). It seems quite possible that even
if all of the major foci were removed (something that has yet to be
accomplished), rats would still be able to use small differences that are
likely to persist after bulb damage to support a reinforced discrimination.
In many ways, the use of habituation/dishabituation
analyses is superior to the use of differential reinforcement in experiments
attempting to understand the olfactory code. Not only is the procedure accomplished in a minimal number
of trials (5 or 6, as opposed to many hundreds of conditioning trials), but it
also has the potential for showing a graded similarity in perception of closely
related odorants, thereby allowing correlations with neurobiological data. Indeed, correlating the differences in
perceptual response, as measured by the spontaneous discrimination test with
the differences in 2-DG patterns generated by aliphatic acids of different
carbon number (Johnson et al., 1999) revealed a correlation coefficient of
0.92(Cleland, et al., in press).
The high correlation of the major glomerular modules with spontaneous
discriminations suggests that this approach may be a valuable tool for
the understanding of the olfactory code.
On the other hand, using differential reinforcement to assess the
potential impact of the small differences in glomerular responses may inform us
about the limits of olfactory processing in rats.
Literature cited
Arctander S. (1994). Perfume and Flavor Chemicals (Aroma Chemicals). Carol Stream, IL: Allured Publishing Company.
Cleland, T.A., Morse, A.,
Yue, E.L. and Linster, C.
Behavioral models for odor similarity. Behavioral Neuroscience (in
press)
Friedman L, Miller JG (1971) Odor
incongruity and chirality. Science 172:1044-1046
Hbener F, Laska M.
2001. A two-choice discrimination method to assess olfactory performance in
pigtailed macaques, Macaca nemestrina.
Physiol Behav 72:511-519.
Joerges J, Kttner A,
Galizia CG, Menzel R. (1997)
Representations of odours and odour mixtures visualized in the honeybee
brain. Nature 387:285-288.
Johnson BA, Leon M. (2000) Modular representations of
odorants in the glomerular layer of the rat olfactory bulb and the effects of
stimulus concentration. J Comp Neurol, 409:495-509.
Johnson BA, Woo CC,
Hingco EE, Pham KL, Leon M. (1999)
Multidimensional chemotopic responses to n-aliphatic acid odorants in the rat
olfactory bulb. J
Comp Neurol 409:529-548.
Johnson BA, Woo CC, Leon
M. (1998) Spatial coding of
odorant features in the glomerular layer of the rat olfactory bulb. J Comp Neurol 393:457-471.
Laska M, Galizia CG. (2001) Enantioselectivity of odor
perception in honeybees (Apis mellifera carnica). Behav Neurosci. 115:632-639.
Laska, M, Galizia, CG, Giurfa, M,
Menzel, R (1999a). Olfactory discrimination ability and odor structure-activity
relationships in honeybees. Chem Senses, 24(4), 429-438.
Laska M, Liesen A, Teubner P
(1999b) Enantioselectivity of odor perception in squirrel monkeys and humans.
Am J Physiol 277:R1098-R1103.
Laska M, Teubner P (1999) Olfactory discrimination ability of
human subjects for ten pairs of enantiomers. Chem Senses 24:161-170.
Leitereg TJ, Guadagni DG, Harris J,
Mon TR, Teranishi R (1971) Evidence for the difference between the odours of
the optical isomers (+)- and (-)-carvone. Nature 230:455-456.
Linster C, Hasselmo
ME. (1999) Behavioral responses to
aliphatic aldehydes can be predicted from known electrophysiological responses
of mitral cells in the olfactory bulb.
Physiol Behav 66:497-502.
Linster C,
Johnson BA, Morse A, Yue E, Xu Z,
Hingco EE, Choi Y, Choi M, Messiha A,
Leon M. Perceptual
correlates of neural representations evoked by odorant enantiomers. J Neurosci, in press.
Linster C, Smith BH. (1999) Generalization
between binary odor mixtures and their components in the rat. Physiol Behav 66:701-707.
Lu XC, Slotnick
BM (1998) Olfaction in rats with extensive
lesions of the olfactory bulbs: implications for odor coding. Neuroscience. 84:849-866.
Rubin RD, LC Katz. (2001) Spatial coding of enantiomers in the rat olfactory
bulb. Nature Neurosci. 4:355-356.
Sachse S, Rappert A, Galizia CG
(1999) The spatial representation of chemical structures in the antennal lobe
of honeybees: steps towards the olfactory code. Eur J Neurosci 11:3970-3982.
Slotnick B. (2001) Animal cognition and the rat
olfactory system. Trends Cogn
Sci. 5:216-222.
Figure legends
Figure 1. Rolled-out contour charts of the entire
glomerular layer indicate the distribution of p values in two-tailed t tests
performed at each position within the arrays. Warm colors signify locations where the (-)-enantiomer evoked
potentially greater uptake. Cool
colors indicate locations where uptake for the (+)-enantiomer potentially
exceeded that for the (-)-enantiomer.

Figure 2. The mean percent correct
responses to odorants that had previously been rewarded, shown as a function of
trial number. Asterisks indicate a
response that is significantly different from the response to the control
odorants.
